SPR 672

OCTOBER 2013

Development of a Traf ic
Data Input System in
Arizona for the MEPDG

Arizona Department of Transportation Research Center

Development of a Traffic
Data Input System in
Arizona for the MEPDG

Final Report 672
October 2013

Prepared by:
Michael I. Darter
Leslie Titus-Glover
Dean J. Wolf
Applied Research Associates, Inc.
100 Trade Centre Dr., Suite 200
Champaign, IL 61820

Prepared for:
Arizona Department of Transportation
206 S. 17th Ave.
Phoenix, AZ 85007
in cooperation with
U.S. Department of Transportation
Federal Highway Administration

This report was funded in part through grants from the Federal Highway Administration, U.S. Department of
Transportation. The contents of this report reflect the views of the authors, who are responsible for the facts and
the accuracy of the data, and for the use or adaptation of previously published material, presented herein. The
contents do not necessarily reflect the official views or policies of the Arizona Department of Transportation or
the Federal Highway Administration, U.S. Department of Transportation. This report does not constitute a
standard, specification, or regulation. Trade or manufacturers’ names that may appear herein are cited only
because they are considered essential to the objectives of the report. The U.S. government and the State of
Arizona do not endorse products or manufacturers.

Technical Report Documentation Page
1. Report No.

2. Government Accession No.

3. Recipient's Catalog No.

FHWA-AZ-13-672
4. Title and Subtitle

5. Report Date

Development of a Traffic Data Input System in Arizona for the MEPDG

October 2013
6. Performing Organization Code

7. Author

8. Performing Organization Report No.

Michael I. Darter, Leslie Titus-Glover, Dean J. Wolf
9. Performing Organization Name and Address

10. Work Segment No.

Applied Research Associates, Inc.
100 Trade Centre Dr., Suite 200
Champaign, IL 61820

11. Contract or Grant No.

SPR-PL1(175) 672

12. Sponsoring Agency Name and Address

13.Type of Report & Period Covered

Research Center
Arizona Department of Transportation
206 S. 17th Ave.
Phoenix, AZ 85007

FINAL October 2009-October 2011
14. Sponsoring Agency Code

15. Supplementary Notes

Prepared in cooperation with the U.S. Department of Transportation, Federal Highway Administration
16. Abstract

Accurate traffic data is one of the key data elements required for the cost-effective design of all rehabilitation and reconstruction of
pavement structures. This research study addresses the collection, preparation, and use of traffic data required for pavement design
by the Arizona Department of Transportation (ADOT), focusing on data required as inputs for the American Association of State
Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG) design procedures.
ADOT’s current traffic data collection and preparation processes are not adequate to meet the needs of the MEPDG procedure, and
improvements are needed. These improvements include enhanced volume, classification, and weight data collection for vehicles,
processing data and performing quality assurance checks, and the preparation/analysis of the data for use in the MEPDG. Use of the
MEPDG in Arizona will require (1) an annual flow of updated key traffic data and (2) the ability to collect on-site (MEPDG Level
1) data in a timely manner for key projects.
An action plan (Chapter 8) calls for the establishment of an Arizona Traffic Segment Database that includes all state highways (or
the expansion of an existing traffic database). This database would include all traffic inputs required for the AASHTO MEPDG and
AASHTO 1993 design procedures, as well as ADOT pavement management activities. Traffic segments would be identified by
beginning and ending milepost numbers and global positioning system (GPS) coordinates along each highway.
The researchers propose, and have partly developed, a system for traffic data collection for the MEPDG in Arizona. Level 1 data
collection procedures are provided for selected traffic inputs. ADOT’s traffic data collection group will need to develop a process
for collecting Level 1 data in a timely manner for important projects requested from the pavement design group. This report also
discusses recommended Level 2 and Level 3 inputs, which were prepared based on the best historical data available. These data
represent a good initial set of inputs that can be used over the next few years. However, the inputs should be updated annually using
improved data collection methods beginning as soon as possible.

17. Key Words

18. Distribution Statement

Traffic, trucks, axle weights, WIM, vehicle classification,
design, MEPDG

Document is available to the U.S.
public through the National
Technical Information Service,
Springfield, Virginia 22161

19. Security Classification

21. No. of Pages

Unclassified

Form DOT F 1700.7

20. Security Classification

Unclassified

358

23. Registrant's Seal

22. Price

SI* (MODERN METRIC) CONVERSION FACTORS
APPROXIMATE CONVERSIONS TO SI UNITS
Symbol

When You Know

Multiply By
LENGTH

in
ft
yd
mi

inches
feet
yards
miles

in
2
ft
2
yd
ac
2
mi

2

square
square
square
acres
square

fl oz
gal
3
ft
3
yd

fluid ounces
gallons
cubic feet
cubic yards

oz
lb
T

ounces
pounds
short tons (2000 lb)

o

Fahrenheit

fc
fl

foot-candles
foot-Lamberts

lbf
2
lbf/in

poundforce
poundforce per square inch

25.4
0.305
0.914
1.61

To Find

Symbol

millimeters
meters
meters
kilometers

mm
m
m
km

square millimeters
square meters
square meters
hectares
square kilometers

mm
2
m
2
m
ha
2
km

milliliters
liters
cubic meters
cubic meters
3
shown in m

mL
L
3
m
3
m

grams
kilograms
megagrams (or "metric ton")

g
kg
Mg (or "t")

AREA
inches
feet
yard

645.2
0.093
0.836
0.405
2.59

miles

2

VOLUME
29.57
3.785
0.028
0.765
NOTE: volumes greater than 1000 L shall be

MASS
28.35
0.454
0.907

TEMPERATURE (exact degrees)
F

5 (F-32)/9
or (F-32)/1.8

Celsius

o

lux
2
candela/m

lx
2
cd/m

C

ILLUMINATION
10.76
3.426

FORCE and PRESSURE or STRESS
4.45
6.89

newtons
kilopascals

N
kPa

APPROXIMATE CONVERSIONS FROM SI UNITS
Symbol

When You Know

mm
m
m
km

millimeters
meters
meters
kilometers

Multiply By
LENGTH
0.039
3.28
1.09
0.621

To Find

Symbol

inches
feet
yards
miles

in
ft
yd
mi

AREA
2

mm
2
m
2
m
ha
2
km

square millimeters
square meters
square meters
hectares
square kilometers

0.0016
10.764
1.195
2.47
0.386

square
square
square
acres
square

inches
feet
yards
miles

2

in
2
ft
2
yd
ac
2
mi

VOLUME
mL
L
3
m
3
m

milliliters
liters
cubic meters
cubic meters

0.034
0.264
35.314
1.307

g
kg
Mg (or "t")

grams
kilograms
megagrams (or "metric ton")

o

Celsius

fluid ounces
gallons
cubic feet
cubic yards

fl oz
gal
3
ft
3
yd

ounces
pounds
short tons (2000 lb)

oz
lb
T

MASS
0.035
2.202
1.103

TEMPERATURE (exact degrees)
C

1.8C+32

Fahrenheit

o

foot-candles
foot-Lamberts

fc
fl

F

ILLUMINATION
lx
2
cd/m

lux
2
candela/m

N
kPa

newtons
kilopascals

0.0929
0.2919

FORCE and PRESSURE or STRESS
0.225
0.145

poundforce
poundforce per square inch

lbf
2
lbf/in

*SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E380.
(Revised March 2003)

CONTENTS
CHAPTER 1. INTRODUCTION ................................................................................................ 1
Brief Background ...................................................................................................................... 1
Objectives ................................................................................................................................. 2
Brief Summary of Findings ...................................................................................................... 2
Organization of Report ............................................................................................................. 3
CHAPTER 2. CURRENT AND FUTURE TRAFFIC DATA REQUIREMENTS FOR
PAVEMENT DESIGN ........................................................................................................... 5
Current ADOT Traffic Data Requirements .............................................................................. 5
MEPDG Traffic Data Requirements ....................................................................................... 10
CHAPTER 3. FRAMEWORK FOR DEVELOPING THE ADOT MEPDG TRAFFIC
DATA INPUT SYSTEM ...................................................................................................... 23
Step 1: Traffic Data Identification and Assembly .................................................................. 23
Step 2: Traffic Data Processing, Review, Identification of Anomalies and Error,
and Data Cleansing ................................................................................................................. 29
Step 3: Statistical Analysis to Assign Measured Traffic Data into Clusters with Similar
Characteristics and Distribution Patterns ................................................................................ 37
Step 4: Determination of Optimum Number of Clusters Within Arizona .............................. 40
Step 5: Performance of Sensitivity Analysis and Interpretation of Sensitivity Analysis
Results ..................................................................................................................................... 40
Step 6: Development of Default Statewide Level 2/3 Traffic Inputs ..................................... 41
CHAPTER 4. STATISTICAL CLUSTER ANALYSIS .......................................................... 43
Vehicle Class Distribution ...................................................................................................... 43
Hourly Truck Traffic Distribution .......................................................................................... 54
Axle Load Distribution ........................................................................................................... 66
Axles Per Truck ...................................................................................................................... 75
CHAPTER 5. SENSITIVITY ANALYSIS ............................................................................... 79
Description of Baseline Pavement Designs ............................................................................ 79
MEPDG Traffic Inputs Used for Sensitivity Analysis ........................................................... 82
Sensitivity Analysis Results.................................................................................................... 85
CHAPTER 6. DEVELOPMENT OF STATEWIDE LEVEL 2/3 MEPDG TRAFFIC
INPUTS .................................................................................................................................. 95
Vehicle Class Distribution ...................................................................................................... 95
Hourly Truck Distribution ...................................................................................................... 95
Monthly Adjustment Factor .................................................................................................... 96
Axle Load Distribution ........................................................................................................... 97
Axles Per Truck ...................................................................................................................... 97
CHAPTER 7. DETAILED SYSTEM FOR ADOT TRAFFIC DATA INPUTS FOR
THE MEPDG DESIGN PROCESS .................................................................................. 115
Overall Summary of Arizona Traffic Data Input System ..................................................... 115
Detailed Description of Traffic Segment Database .............................................................. 115

iii

CHAPTER 8. ACTION PLAN ................................................................................................ 143
Locations of WIM Equipment .............................................................................................. 145
Type of WIM Equipment ...................................................................................................... 148
Cost of Equipment ................................................................................................................ 150
Recommended Business Process Overview ......................................................................... 151
REFERENCES .......................................................................................................................... 153
APPENDIX A. REVIEW OF HISTORICAL ADOT TRAFFIC DATA
COLLECTION PRACTICES ........................................................................................... 153
APPENDIX B. SUMMARY OF VCD DATA USED FOR ANALYSIS .............................. 171
APPENDIX C. SUMMARY OF HOURLY TRUCK DISTRIBUTION DATA USED
FOR ANALYSIS ................................................................................................................. 205
APPENDIX D. SUMMARY OF MAF DATA USED FOR ANALYSIS ............................. 217
APPENDIX E. SUMMARY OF ALD DATA USED FOR ANALYSIS .............................. 261
APPENDIX F. SUMMARY OF AXLES-PER-TRUCK DATA USED FOR
ANALYSIS .......................................................................................................................... 305
APPENDIX G. RECOMMENDED ADOT BUSINESS PROCESS OVERVIEW
FOR MEPDG AND PAVEMENT MANAGEMENT SYSTEM .................................... 335

iv

LIST OF FIGURES
Figure 1. Illustration of Vehicle Class Distribution (FHWA Vehicle Classes 4 through 13) for the
Selected LTPP Sites. ................................................................................................................. 7
Figure 2. Comparison between Concrete and Asphalt Pavement ESALs. ..................................... 8
Figure 3. Comparison between Flexible Pavement ESALs and Computed ESALs-per-Truck
Ratios (ARA, 2009; Alavi and Senn, 1999). ............................................................................ 9
Figure 4. Comparison between Rigid Pavement ESALs and Computed ESALs-per-Truck
Ratios (ARA, 2009; Alavi and Senn, 1999). ............................................................................ 9
Figure 5. Comparison between Computed Rural and Urban Flexible Pavement
ESALs-per-Truck Ratios. ....................................................................................................... 10
Figure 6. Example of Distance from the Outer Edge of the Wheel to the Pavement Marking. ... 18
Figure 7. Illustration of Truck Wheelbase Definition. .................................................................. 19
Figure 8. Axle Wheel Configuration Inputs (Average Axle Width Edge to Edge), Dual Tire
Spacing, Axle Wheel Spacing (Tandem, Tridem, and Quad Axles). ..................................... 19
Figure 9. Locations of the Arizona ATR Data Collection Sites. .................................................. 25
Figure 10. LTPP Sites across Arizona. ......................................................................................... 27
Figure 11. Plot of Vehicle Class Distribution for Site 4_0100 (Prior to September 2001). ......... 32
Figure 12. Plot of Vehicle Class Distribution for Site 4_0100 (Prior to and After September
2001) Showing Significant Reduction in Class 9 Trucks. ...................................................... 32
Figure 13. Plot of Hourly Truck Distribution for Site 4 100070. ................................................. 33
Figure 14. Plot of Monthly Adjustment Factors for LTPP 0100 (Class 4 Vehicles Only). .......... 33
Figure 15. Plot of Vehicle Class Distribution for LTPP 1001. ..................................................... 34
Figure 16. Plot Showing Number of Single Axles per Truck for LTPP 0500. ............................. 34
Figure 17. Plot Showing Tandem-Axle Load Distribution for LTPP 1001. ................................. 35
Figure 18. Typical Arizona Interstate Highway Single Peak VCD. ............................................. 45
Figure 19. Typical Arizona Non-Interstate Highway Double Peak VCD Found in Urban
Areas or Other Rural Highways. ............................................................................................. 46
Figure 20. Plot of VCD for Rural Principal Arterial – Interstate (Project 4_0200R, I-10,
Maricopa County). .................................................................................................................. 49
Figure 21. Plot of VCD for Rural Principal Arterial – Interstate (Project 4_1024, I-40,
Yavapai County). .................................................................................................................... 50
Figure 22. Plot of VCD for Rural Principal Arterial – Other (Project 4_6055_R, SR 85,
Maricopa County). .................................................................................................................. 50
Figure 23. Plot of VCD for Rural Principal Arterial – Other (Project 4_102094, U.S. 93,
Yavapai County). .................................................................................................................... 51
Figure 24. Plot of VCD for Urban Principal Arterial (Project 4_101602, SR 303, Maricopa
County). .................................................................................................................................. 51
Figure 25. Plot of VCD for Urban Principal Arterial (Project 4_7079_R, SR 101, Maricopa
County). .................................................................................................................................. 52
Figure 26. Plot of VCD for Site Rural Major Arterial (Project 4_100854, SR 79,
Pinal County). ......................................................................................................................... 52
Figure 27. Plot of VCD for Rural Major Arterial (Project 4_101622, SR 347, Pinal County). ... 53
Figure 28. Plot of VCD for Rural Major Collector (Project 4_102230, U.S. 191, Graham
County). .................................................................................................................................. 53
Figure 29. Plot of VCD for Rural Major Collector (Project 4_100767, SR 72, La Paz County). 54

v

Figure 30. Location of AVC Sites in Arizona Used in the Hourly Traffic Analysis. ................... 55
Figure 31. Illustration of a Cluster Analysis for “Correlation Coefficient” to Distinguish
between Hourly Truck Distributions. ..................................................................................... 56
Figure 32. Plot of Typical Rural Truck Hourly Distribution for Site 4_100537 Located in
Coconino County on I-40........................................................................................................ 58
Figure 33. Plot of Typical Urban Truck Hourly Distribution for Site 4_100800 Located in
Urban Pima County (Tucson) on SR 77. ................................................................................ 58
Figure 34. Plot of Relatively Flat Hourly Distribution for Site 4_100070 from a Far-Western,
Long-Haul Section on I-10 in the Desert. ............................................................................... 59
Figure 35. Plot of Three Hourly Truck Distributions. .................................................................. 59
Figure 36. Locations of AVC Sites Used in the Analysis of Monthly Truck Adjustment
Factors. .................................................................................................................................... 61
Figure 37. Results from the Correlation Coefficient Method for Monthly Truck Adjustment
Factors. .................................................................................................................................... 63
Figure 38. Plot of MAF for Site 4_100188 (Vehicle Class 5), I-10 in Cochise County............... 64
Figure 39. Plot of MAF for Site 4_100188 (Vehicle Class 9), I-10 in Cochise County............... 64
Figure 40. Plot of MAF for Site 4_100541 (Vehicle Class 5), I-40 in Coconino County. ........... 65
Figure 41. Plot of MAF for Site 4_100541 (Vehicle Class 9), I-40 in Coconino County. ........... 65
Figure 42. Locations of the LTPP Sites with WIM Data.............................................................. 66
Figure 43. Typical Arizona Highway Class 5 Truck Single-Axle Load Distribution. ................. 67
Figure 44. Typical Arizona Highway Class 9 Truck Single-Axle Load Distribution. ................. 68
Figure 45. Typical Arizona Highway Class 9 Truck Tandem-Axle Load Distribution. .............. 68
Figure 46. Single-Axle Load Distribution for Truck Class 5. ...................................................... 72
Figure 47. Single-Axle Load Distribution for Truck Class 9. ...................................................... 72
Figure 48. Tandem-Axle Load Distribution for Truck Class 9. ................................................... 73
Figure 49. Map of Sites Used for the Axles-Per-Truck Analysis. ................................................ 75
Figure 50. Plot of Axles per Truck for Site 4_0500 (Vehicle Class 9). ........................................ 77
Figure 51. Plot of Axles per Truck for Site 4_1002 (Vehicle Class 9). ........................................ 77
Figure 52. Plot of Axles per Truck for Site 4_1007 (Vehicle Class 9). ........................................ 78
Figure 53. Plot of Axles per Truck for Site 4_6055 (Vehicle Class 9). ........................................ 78
Figure 54. Baseline Traffic Volume Inputs Used for Sensitivity Analysis. ................................. 80
Figure 55. Location of Climate Stations for Baseline HMA Pavement Project. .......................... 80
Figure 56. Location of Climate Stations for Baseline HMA Pavement Project. .......................... 81
Figure 57. Plot of VCD for Clusters 1 and 2 and the MEPDG Default. ....................................... 82
Figure 58. Plot of Single ALD for Clusters 1, 2, and 3 (Class 5 Trucks Only). ........................... 83
Figure 59. Plot of Single ALD for Clusters 1 and 2 (Class 9 Trucks Only). ................................ 83
Figure 60. Plot of Tandem ALD for Clusters 1 and 2 (Class 9 Trucks Only). ............................. 84
Figure 61. Plot of Hourly Distribution for Clusters 1 and 2 and the MEPDG Default. ............... 84
Figure 62. Plot Showing the Effect of VCD Clusters 1 and 2 on New HMA Pavement
Alligator Cracking. ................................................................................................................. 85
Figure 63. Plot Showing the Effect of VCD Clusters 1 and 2 on New HMA
Pavement Rutting. ................................................................................................................... 86
Figure 64. Plot Showing the Effect of VCD Clusters 1 and 2 on New HMA Pavement IRI. ...... 86
Figure 65. Plot Showing the Effect of VCD Clusters 1 and 2 on New JPCP
Transverse Cracking. .............................................................................................................. 87
Figure 66. Plot Showing the Effect of VCD Clusters 1 and 2 on New JPCP Faulting................. 87

vi

Figure 67. Plot Showing the Effect of VCD Clusters 1 and 2 on New JPCP IRI......................... 88
Figure 68. Plot Showing the Effect of ALD Clusters 1 through 3 on New HMA Pavement
Alligator Cracking. ................................................................................................................. 89
Figure 69. Plot Showing the Effect of ALD Clusters 1 through 3 on New HMA Pavement
Rutting..................................................................................................................................... 89
Figure 70. Plot Showing the Effect of ALD Clusters 1 through 3 on New HMA Pavement IRI. 90
Figure 71. Plot Showing the Effect of ALD Clusters 1 through 3 on New JPCP Transverse
Cracking. ................................................................................................................................. 90
Figure 72. Plot Showing the Effect of ALD Clusters 1 through 3 on New JPCP Faulting. ......... 91
Figure 73. Plot Showing the Effect of ALD Clusters 1 through 3 on New JPCP IRI. ................. 91
Figure 74. Plot Showing the Effect of Hourly Distribution Clusters 1 and 2 on New JPCP
Transverse Cracking. .............................................................................................................. 92
Figure 75. Plot Showing the Effect of Hourly Distribution Clusters 1 and 2 on New JPCP
Faulting. .................................................................................................................................. 93
Figure 76. Plot Showing the Effect of Hourly Distribution Clusters 1 and 2 on
New JPCP IRI. ........................................................................................................................ 93
Figure 77. Map of Sites Where Lateral Wander of Trucks Was Measured in Arizona. ............. 111
Figure 78. Histogram and Fitted Normal Distribution Curve Showing the Distribution of
Wheel Lateral Wander. ......................................................................................................... 112
Figure 79. Typical Arizona Rural 24-Hour Distribution of Trucks. ........................................... 124
Figure 80. Typical Arizona 24-Hour Urban Distribution of Trucks. .......................................... 124
Figure 81. Typical 24-Hour Long-Haul Distance Desert Distribution of Trucks....................... 125
Figure 82. Map of Recommended WIM Sites. ........................................................................... 146
Figure 83. TDC/Piezo GVW Distribution. ................................................................................. 148
Figure 84. LTPP SPS-2 GVW Distribution. ............................................................................... 149
Figure 85. Recommended Business Process Overview. ............................................................. 151

vii

LIST OF TABLES
Table 1. Estimate of Overall ESALs-per-Truck Factor for ADOT (Alavi & Senn, 1999)............. 6
Table 2. LTPP Sites from Which WIM Data Were Assembled and Used for Analysis................. 7
Table 3. Computed ESALs for Several Sites in Arizona (ARA, 2004). ......................................... 8
Table 4. Initial Year Traffic Data. ................................................................................................ 12
Table 5. Truck Traffic Volume Adjustment Factors. ................................................................... 13
Table 6. Descriptions of MEPDG Default TTC Groups (ARA, 2004). ....................................... 15
Table 7. Default Vehicle Class Distribution for Each MEPDG TTC Group (ARA, 2004).......... 16
Table 8. Recommendations for Selecting MEPDG TTC Groups Based on Highway
Functional Class (ARA, 2004). ............................................................................................... 17
Table 9. Truck Traffic Volume Other Adjustment Factors. ......................................................... 17
Table 10. Recommended Level of Input for MEPDG Traffic Input Variables. ........................... 20
Table 11. Arizona ATR Sites Used in the Analysis of VCD. ....................................................... 24
Table 12. LTPP Data Tables from Which Data Were Obtained for Analysis. ............................. 26
Table 13. Detailed Description of LTPP Sites in Arizona. ........................................................... 28
Table 14. Arizona Truck Wheelbase Distribution at Two Sites (Classes 8 through 13 Only). .... 30
Table 15. Summary of Traffic Data Availability for Analysis in Arizona. .................................. 36
Table 16. Criteria for Selecting the Optimum Number of Clusters. ............................................. 39
Table 17. National Highway TTC VCD Defaults in the MEPDG. .............................................. 44
Table 18. VCD TTCs Based on Arizona Data That Are Closely Related to the
National TTCs. ........................................................................................................................ 44
Table 19. Differences between MEPDG and Arizona TTC Recommendations for VCD. .......... 45
Table 20. Selection Criteria for Level 3 MEPDG Arizona TTCs Based on Functional Class. .... 46
Table 21. Summary of Cluster Analysis for VCD Using ADOT and LTPP Datasets.................. 47
Table 22. Matching Cluster 1 to TTC 2 and Cluster 2 to TTC 12. ............................................... 49
Table 23. Summary of Sites and Clusters Determined for Hourly Truck Traffic
Distribution. ............................................................................................................................ 57
Table 24. AVC Sites Used in the Monthly Truck Adjustment Factors. ....................................... 62
Table 25. Summary of Outlier Data Excluded from the Cluster Analysis. .................................. 70
Table 26. Summary of Cluster Analysis for ALD Using ADOT and LTPP Datasets. ................. 74
Table 27. Summary of All Sites Used in the Axles-per-Truck Cluster Analysis. ........................ 76
Table 28. HMA Pavement Materials Properties. .......................................................................... 79
Table 29. JPCP Materials Properties. ........................................................................................... 81
Table 30. MEPDG Traffic Input Data Clusters Used for Sensitivity Analysis. ........................... 82
Table 31. Summary of Sensitivity Results for VCD..................................................................... 88
Table 32. Summary of Sensitivity Results for ALD. .................................................................... 92
Table 33. Recommended MEPDG VCD Inputs for Level 2/3 Design in Arizona. ...................... 95
Table 34. Recommended MEPDG Hourly Truck Distribution Input for Design in Arizona. ...... 96
Table 35. Recommended MEPDG MAF Input for Design in Arizona. ....................................... 97
Table 36. Recommended Cluster 1 Single Axle MEPDG ALD Input for Design
in Arizona................................................................................................................................ 98
Table 37. Recommended Cluster 1 Tandem Axle MEPDG ALD Input for Design
in Arizona................................................................................................................................ 99
Table 38. Recommended Cluster 1 Tridem Axle MEPDG ALD Input for Design
in Arizona.............................................................................................................................. 100

viii

Table 39. Recommended Cluster 1 Quad Axle MEPDG ALD Input for Design in Arizona. .... 101
Table 40. Recommended Cluster 2 Single Axle MEPDG ALD Input for Design
in Arizona.............................................................................................................................. 102
Table 41. Recommended Cluster 2 Tandem Axle MEPDG ALD Input for Design
in Arizona.............................................................................................................................. 103
Table 42. Recommended Cluster 2 Tridem Axle MEPDG ALD Input for Design
in Arizona.............................................................................................................................. 104
Table 43. Recommended Cluster 2 Quad Axle MEPDG ALD Input for Design in Arizona. .... 105
Table 44. Recommended Cluster 3 Single Axle MEPDG ALD Input for Design
in Arizona.............................................................................................................................. 106
Table 45. Recommended Cluster 3 Tandem Axle MEPDG ALD Input for Design
in Arizona.............................................................................................................................. 107
Table 46. Recommended Cluster 3 Tridem Axle MEPDG ALD Input for Design
in Arizona.............................................................................................................................. 108
Table 47. Recommended Cluster 3 Quad Axle MEPDG ALD Input for Design
in Arizona.............................................................................................................................. 109
Table 48. Recommended MEPDG Axles-per-Truck Statistics Default Input for Design
in Arizona.............................................................................................................................. 110
Table 49. Wheelbase Distribution............................................................................................... 113
Table 50. ADOT Comprehensive Traffic Data Input System for the MEPDG. ......................... 116
Table 51. Traffic Volume Inputs Required for the MEPDG. ..................................................... 117
Table 52. Recommended Selection Criteria for Level 3 Arizona TTCs Based on Highway
Functional Class. ................................................................................................................... 120
Table 53. Recommended Level 3 VCDs for Specific Arizona TTCs......................................... 120
Table 54. Percent Trucks in Design Lane for Arizona Sections. ................................................ 121
Table 55. Summary of 24-Hour Truck Distributions Recommended for Arizona MEPDG
for Input Level 2/3 by Rural and Urban Functional Class. ................................................... 125
Table 56. Traffic Weight Inputs Required. ................................................................................. 126
Table 57. Summary of Level 2/3 Single Axle ALD Recommended for Arizona Rural
Principal Arterials, Interstate. ............................................................................................... 127
Table 58. Summary of Level 2/3 Tandem Axle ALD Recommended for Arizona Rural
Principal Arterials, Interstate. ............................................................................................... 128
Table 59. Summary of Level 2/3 Tridem Axle ALD Recommended for Arizona Rural
Principal Arterials, Interstate. ............................................................................................... 129
Table 60. Summary of Level 2/3 Quad Axle ALD Recommended for Arizona Rural
Principal Arterials, Interstate. ............................................................................................... 130
Table 61. Summary of Level 2/3 Single Axle ALD Recommended for Arizona Urban
Freeways and Rural Minor Arterials/Collectors. .................................................................. 131
Table 62. Summary of Level 2/3 Tandem Axle ALD Recommended for Arizona Urban
Freeways and Rural Minor Arterials/Collectors. .................................................................. 132
Table 63. Summary of Level 2/3 Tridem Axle ALD Recommended for Arizona Urban
Freeways and Rural Minor Arterials/Collectors. .................................................................. 133
Table 64. Summary of Level 2/3 Quad Axle ALD Recommended for Arizona Urban
Freeways and Rural Minor Arterials/Collectors. .................................................................. 134
Table 65. Summary of Level 2/3 Single Axle ALD Recommended for Arizona Rural
Principal Arterials, Non-Interstate. ....................................................................................... 135

ix

Table 66. Summary of Level 2/3 Tandem Axle ALD Recommended for Arizona Rural
Principal Arterials, Non-Interstate. ....................................................................................... 136
Table 67. Summary of Level 2/3 Tridem Axle ALD Recommended for Arizona Rural
Principal Arterials, Non-Interstate. ....................................................................................... 137
Table 68. Summary of Level 2/3 Quad Axle ALD Recommended for Arizona Rural
Principal Arterials, Non-Interstate. ....................................................................................... 138
Table 69. Traffic Geometric Inputs Required. ............................................................................ 139
Table 70. Recommended Values of Axles per Truck for Arizona Design. ................................ 140
Table 71. Other Traffic Inputs Required..................................................................................... 142
Table 72. Action Plan for Development of an ADOT Comprehensive Traffic Data Input
System for the MEPDG. ....................................................................................................... 144
Table 73. Action Plan Summary of What, Who, and When. ...................................................... 144
Table 74. Recommended WIM Sites: New, Upgrades, and POEs. ............................................ 147
Table 75. Functional Class for Recommended WIM sites. ........................................................ 147
Table 76. Options for Meeting the Recommended WIM Site Requirements. ............................ 147
Table 77. TDC/LTPP Weight Measurement Comparison. ......................................................... 149
Table 78. Axle Spacing Measurement Comparison. .................................................................. 149
Table 79. Performance and Cost of WIM Equipment. ............................................................... 150

x

ACRONYMS AND ABBREVIATIONS
AADT
AADTT
AASHO
AASHTO
ADOT
ADR
ALD
ATLAS
ATR
ATRC
AVC
CCC
ESAL
FHWA
GPS
GPS
GVW
HMA
IRI
JPCP
LDF
LEF
LTPP
MEPDG
MAF
MP
MPD
MVD
NCHRP
PCC
POE
PSF
PST2
R2
SHRP
SPS
TPD
TTC
VAR
VCD
WIM

Annual average daily traffic
Annual average daily truck traffic
American Association of State Highway Officials
American Association of State Highway and Transportation Officials
Arizona Department of Transportation
Automatic data recorder
Axle load distribution
Advanced Traffic Loading and Analysis System
Automated traffic recorder
Arizona Transportation Research Center
Automatic vehicle classification
Cubic clustering criterion
Equivalent single-axle load
Federal Highway Administration
Global positioning system
General Pavement Studies
Gross vehicle weight
Hot mix asphalt
International Roughness Index
Jointed plain concrete pavement
Load distribution factor
Load equivalency factor
Long-Term Pavement Performance
Mechanistic-Empirical Pavement Design Guide
Monthly adjustment factors
Milepost
Multimodal Planning Division
Motor Vehicle Division
National Cooperative Highway Research Program
Portland cement concrete
Port-of-entry
Pseudo F-value
Pseudo t2 value
Cumulative and partial squared multiple correlation
Strategic Highway Research Program
Specific Pavement Studies
Transportation Planning Division
Truck traffic classification
Eigenvalue and associated variance
Vehicle class distribution
Weigh-in-motion

xi

xii

CHAPTER 1. INTRODUCTION
The Arizona Department of Transportation (ADOT) maintains over 7,000 miles of highways that
require new construction, reconstruction of existing alignments, maintenance, resurfacing, and
rehabilitation, including lane widening, to carry future heavy truck traffic. Approximately onehalf of the ADOT highway construction budget is dedicated to pavement. Accurate estimates of
traffic are important for the cost-effective design of new and rehabilitated pavement.
This research study, SPR-672, addresses the collection, preparation, and use of traffic data for
the design of new and rehabilitated pavement. The study focuses primarily on traffic data that
ADOT will require for implementing the American Association of State Highway and
Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG)
(AASHTO, 2008).
BRIEF BACKGROUND
Currently, the only traffic data available to ADOT’s Pavement Design Section for designing
pavements in Arizona are the annual average daily traffic (AADT) data obtained from the ADOT
Multimodal Planning Division (MPD) and the equivalent single-axle load (ESAL) data predicted
by the pavement management software. These predictions are based on the statewide traffic
weight data and vehicle class data collected in the 1990s. Truck volume data have been updated
to the present time to compute growth rate. The future growth rates are based on AADT and does
not account for the types of vehicles in the traffic stream (Federal Highway Administration
[FHWA] Classes 4 through 13). Essentially, the predictions are based on very old classification
and weight information, as well as growth rate based on total traffic growth. Using old data could
lead to significant errors in predictions of traffic loadings, which could affect design and
construction costs. Therefore, it is extremely important that ADOT use current traffic volume,
classification, and weight data based on periodic traffic surveys and measurements.
The MEPDG uses much of the same information as that required for the AASHTO 1993 Guide
for Design of Pavement Structures procedure (AASHTO, 1993), but it requires major changes in
the way ADOT has been acquiring and compiling traffic data. For example, the MEPDG uses
truck axle load spectra data directly instead of calculating ESALs. There are also other inputs
needed that are not currently being collected. Therefore, it is imperative that ADOT has a
comprehensive traffic data input system that is kept current. This type of traffic data input system
will ultimately save the State of Arizona substantial costs by providing more accurate and costeffective designs. After Indiana implemented the MEPDG, they found that they saved a total of
$36 million on 136 projects designed using the MEPDG instead of the 1993 AASHTO procedure
(Nantung, 2011).

1

OBJECTIVES
ADOT initiated efforts to implement the MEPDG (1) as a design tool for new, reconstructed, and
rehabilitated pavements and (2) for conducting forensic evaluation of existing pavements. A key
aspect of the MEPDG implementation effort in Arizona is to develop an MEPDG traffic data
input system. Developing an MEPDG traffic data input system requires:
Identification of MEPDG traffic data input needs.
Evaluation of current ADOT traffic data collection, storage, and analysis practices to
determine whether the system can adequately meet MEPDG traffic data needs.
Performance of quality checks of existing traffic data to determine that they are
reasonable and to identify anomalies.
Development of a detailed action plan to satisfy future MEPDG traffic data needs.
Documentation of findings and recommendations.
BRIEF SUMMARY OF FINDINGS
ADOT’s current traffic data collection and preparation practices require several improvements to
be compatible with MEPDG data needs. For example, ADOT needs to improve data collection
on truck volume and weight, perform quality assurance checks of those data, and prepare/analyze
the data for use in the MEPDG. Using the MEPDG in Arizona will require (1) an annual flow of
updated key traffic data for use as MEPDG Level 2/3 defaults and (2) the ability to collect Level
1 data for key projects being designed.
An action plan in Chapter 8 for developing a traffic data collection system for the MEPDG in
Arizona has been prepared. This plan calls for the establishment of a homogeneous traffic
segment database that includes all highways in Arizona (Interstate, U.S., and state). This
database would include all traffic inputs required for the MEPDG and AASHTO 1993 design
procedures. Traffic segments would include milepost (MP) to MP limits, as well as global
positioning system (GPS) coordinates of the beginning and ending MP. The traffic segment
database would include segment beginning and ending MP and GPS coordinates, traffic volume
inputs, traffic weight inputs, traffic geometry inputs, and other inputs.
This report discusses types of equipment recommended for collecting traffic data based on the
accuracies needed in support of the MEPDG. Cost estimates are provided for the equipment,
installation, site maintenance, equipment calibration, monitoring (data retrieval), and data
analyses.
This report documents procedures to collect Level 1 traffic inputs. Level 2/3 recommended
inputs and defaults are provided based on the best historical data available to date. These data
can be used for MEPDG design for now, but they will need annual updates from improved traffic
volume, classification, and weight stations. ADOT also will need to develop the ability to collect
on-site data for requested key projects where current data are deficient or the size of the project
requires more accurate Level 1 data, as requested by pavement designers.

2

ORGANIZATION OF REPORT
This report provides the results of work accomplished to satisfy the project objectives. Following
is brief description of the report contents:
Chapter 2 summarizes ADOT’s current and future MEPDG traffic data requirements.
Chapter 3 provides a framework for developing an ADOT traffic data input system.
Chapter 4 provides a statistical analysis of traffic input clusters.
Chapter 5 provides the results of a sensitivity analysis.
Chapter 6 provides detailed default recommendations for Level 2/3 statewide traffic
inputs for Arizona.
Chapter 7 provides a detailed input system for ADOT traffic inputs for the MEPDG.
Chapter 8 summarizes an action plan for future work.
Appendix A presents a review of historical ADOT traffic data collection practices.
Appendixes B through F summarize various data used in the analyses for this study,
including vehicle class distribution (VCD), hourly truck distribution, monthly adjustment
factors (MAFs), axle load distribution (ALD), and axles per truck.
Appendix G presents a recommended business process overview for obtaining MEPDG
and pavement management system traffic data.

3

4

CHAPTER 2. CURRENT AND FUTURE TRAFFIC DATA
REQUIREMENTS FOR PAVEMENT DESIGN
CURRENT ADOT TRAFFIC DATA REQUIREMENTS
ESAL Truck Factors
ADOT performs highway pavement design using the 1993 AASHTO Design Guide. The traffic
data required for this procedure are ESALs. The ESAL concept was developed using data
assembled from the American Association of State Highway Officials (AASHO) Road Test
(1958 to 1960), and it establishes a damage relationship between the reference 18,000-lb single
axle with dual tires and different axle types carrying different loads. Design ESALs used for
pavement design are, in effect, a cumulative traffic load summary statistic (over the design
period) representing a mixed stream of axle types and loads converted into an equivalent number
of 18,000-lb single-axle loads totaled over that design period.
The ADOT Pavement Management Section estimates design ESALs using the equation below:
(Alavi and Senn, 1999)
Rigid ESALs:
Yearly ESALseg = 0.5*(AADTseg)*365*(%Trucks)*[(%VC4)*(ESAL4) +
(%VC5)*(ESAL5) + ……… + (%VC13)*(ESAL13)]

(Eq. 1)

Where
ESALseg
AADTseg
%Trucks
%VC#
ESAL#

= total yearly one-way ESALs for all lanes for a network segment
= average annual daily traffic collected by ADOT for the total twoway traffic for all lanes for a single network segment
= percentage of trucks in the traffic system
= percentage of vehicle Classes 4 through 13 in the truck lane determined
from weigh-in-motion (WIM) data
= average ESAL of Classes 4 through 13 in the truck lane determined
from WIM data

Flexible ESALs:
Yearly ESALseg = 0.5*(AADTseg)*365*(%Trucks)*[(%VC4)*(ESAL4) +
(%VC5)*(ESAL5) + ……… + 1.1*(%VC9)*(ESAL9)
+ …………………. + 1.1*%(VC13)*(ESAL13)

(Eq. 2)

Where
ESALseg
AADTseg
%Trucks
%VC#

= total yearly one-way ESALs for all lanes for a network segment
= average annual daily traffic collected by ADOT for the total twoway traffic for all lanes for a single network segment
= percentage of trucks in the traffic system
= percentage of vehicle Classes 4 through 13 in the truck lane determined

5

ESAL#

from WIM data
= average ESALs of Class 4 through 13 vehicles in the truck lane
determined from WIM data

Vehicle Classes 9 through 13 were multiplied by a safety factor of 1.1 for flexible pavements.
In general, AADT and percent of trucks information is provided for each highway segment by
the ADOT Multimodal Planning Division. VCD and ESALs-per-truck information is computed
using data from the nearest appropriate WIM station. For highway segments with only volume
counts data available, Alavi and Senn (1999) developed an overall ESAL per truck factor of 1.08
for flexible pavements, as shown in Table 1.
Table 1. Estimate of Overall ESALs-per-Truck Factor for ADOT (Alavi & Senn, 1999).
Vehicle
Class
4
5
6
7
8
9
10
11
12
13

Average ESALs
per Class
0.87
0.21
0.82
1.64
0.61
1.71
1.31
1.86
0.97
3.73

Average %
Class
4.8
21.8
10.4
2.4
16.1
36.1
2.0
5.1
0.6
0.5
100

ESALs x
Average % Class
0.04
0.04
0.09
0.04
0.10
0.62
0.03
0.09
0.01
0.02
1.08

As part of this study, analyses were performed to update the ESAL truck factors developed in the
early 1990s. This was accomplished using WIM data available from the FHWA Long-Term
Pavement Performance (LTPP) program database (up to 2009 data).
Updated ESAL Truck Factors
Using the most recent WIM data from several Arizona LTPP project sites, a comprehensive
analysis updated the ESAL truck factors published by Alavi and Senn (1999). Those LTPP sites
are shown in Table 2. For each project selected, the following data were assembled:
VCD over all years with data available.
ALD for single, tandem, tridem, and quad axles over all years with data available.
Mean number of single, tandem, tridem, and quad axles per truck over all years with data
available.
For computing ESALs, load equivalency factors (LEF) for 6-inch hot mix asphalt (HMA)
and 9-inch portland cement concrete (PCC) pavement were assumed.
Initial (base year) truck traffic = 1,500 trucks.
Truck traffic annual linear growth rate = 3 percent.
Analysis period = 20 years.
6

Table 2. LTPP Sites from Which WIM Data Were Assembled and Used for Analysis.
LTPP Site
0100
0500
0600
1002
1024
6060
6055
7079

Route No.
U.S.-93
I-8
I-40
I-40
I-40
I-19
SR-85
SR-101

Rural or Urban
Rural
Rural
Rural
Rural
Rural
Rural
Rural and Urban
Urban

County
Mohave
Pinal
Coconino
Yavapai
Yavapai
Santa Cruz
Maricopa
Maricopa

Direction
NB
EB
EB
WB
EB
NB
SB
NB

Milepost
53.6
159
202.2
135.4
107
14.9
141.8
11.9

Figure 1 presents VCD of the selected LTPP projects.
100
90
80

Percent

70
60
50

40
30
20
10
0
4

5
0100
1025

6
0500
1034

7
0600
6055

8
9
Vehicle Class
1001
6060

1002
7079

10

11
1017
7614

12

13

1024

Figure 1. Illustration of Vehicle Class Distribution (FHWA Vehicle Classes 4 through 13)
for the Selected LTPP Sites.
Using the assembled data, the following tasks were performed to obtain estimates of ESALs-pertruck factors:
Estimate cumulative number of trucks (for each individual vehicle class) for the 20-year
analysis period for all of the LTPP sites analyzed.
Estimate cumulative number of flexible and rigid ESALs (for each individual vehicle
class) for the 20-year analysis period for all of the LTPP sites analyzed.
Mean ESALs-per-truck factors for each site, vehicle class, and pavement type.
The results are summarized in Table 3. Several comparisons for the estimated ESALs-per-truck
factors are presented in Figure 2 through Figure 5.

7

Table 3. Computed ESALs for Several Sites in Arizona (ARA, 2004).
LTTP Site
Route No.

Rural
0100
U.S.-93

Rural
0500
I-8

Rural
0600
I-40

Rural
1002
I-40

Rural
1024
I-40

Pinal

Coconino

Yavapai

Yavapai

NB
53.6
1.36
0.13
1.07

EB
159.0
1.09
0.28
0.67

EB
202.2
0.83
0.11
0.78

WB
135.4
1.99
0.65
1.23

EB
107.0
1.79
0.24
0.00

0.37
2.00
1.85
1.73
0.90
1.34
0.95
0.12
0.71

0.40
1.40
2.25
1.50
1.30
9.18
0.93
0.27
0.51

0.36
2.64
1.98
2.31
1.49

1.33
3.85
4.10
2.95
3.94

0.69
2.60
2.36
1.78
1.45

0.67
0.11
0.55

1.43
0.60
0.85

1.21
0.23

0.32
1.28
1.04
1.73
0.81
0.85

0.37
0.92
1.26
1.48
1.19
5.17

0.33
1.62
1.10
2.31
1.40

1.08
2.32
2.17
2.82
3.32

0.61
1.56
1.22
1.77
1.32

County

AC

PCC

Direction
Milepost
4
5
6
7
8
9
10
11
12
13
4
5
6
7
8
9
10
11
12
13

Rural
6060
I-19
Santa
Cruz
NB
14.9
0.82
0.33
0.79

Urban
6055
SR-85

Urban
7079
SR-101

Maricopa

Maricopa

SB
141.8
0.59
0.16
0.99

NB
11.9
0.74
0.26
0.99
2.09
1.02
1.72

1.19
1.89
4.31
1.09
0.75
2.83
0.67
0.32
0.58

0.98
1.39
1.24

0.93
1.18
2.51
1.03
0.65
2.14

0.79
0.88
0.67

0.71
0.48
0.16
0.65

0.65

Note: No current data available for Class 7 trucks; previous values used.

Figure 2. Comparison between Concrete and Asphalt Pavement ESALs.
The ratio of Class 9 trucks for concrete and asphalt is 1.61, which is a typical value.

8

2.36
0.91
3.90
0.63
0.25
0.72
1.38
0.80
1.11
2.32
0.86
2.38

30

ESALs (Flexible), millions

25
20
15
10
5
0
0

2

4

6

8
10
12
14
Number of Trucks, millions

Alavi & Senn 1999

16

18

20

ARA 2009

Figure 3. Comparison between Flexible Pavement ESALs Estimated Using Current 2009
Data (Labeled ARA 2009) and Older Data (Labeled Alavi and Senn 1999).
40

ESALs (Rigid), millions

35
30
25
20
15
10
5
0
0

2

4

6

8
10
12
14
Number of Trucks, millions

Alavi & Senn 1999

16

18

20

ARA 2009

Figure 4. Comparison between Rigid Pavement ESALs Estimated Using Current 2009 Data
(Labeled ARA 2009) and Older Data (Labeled Alavi and Senn 1999).

9

Figure 5. Comparison between Computed Rural and Urban Flexible Pavement ESALs-perTruck Ratios.
The comparisons illustrated in Figure 2 through Figure 5 show the following:
Truck factors have not changed significantly between 1999 and 2009.
There were considerable differences in ESALs-per-truck factors for urban and rural sites,
with rural factors being higher for most truck classes.
Appendix A presents a summary of current ADOT traffic data collection practices.
MEPDG TRAFFIC DATA REQUIREMENTS
The MEPDG software requires (1) base year traffic inputs and traffic volume adjustment factors
and (2) general traffic inputs for pavement design. Descriptions of these traffic input
requirements are presented in this section.
Which MEPDG Level of Input (1 through 3) is Recommended for Each Traffic Variable?
Levels of input to the MEPDG are described briefly as follows:
Level 1.

Level 2.
Level 3.

Direct measure of the traffic input at the project site. Examples include portable
WIM equipment on the project or visual counting of trucks across multiple lanes
at a point on the project.
Correlation of measured traffic inputs with field-measured traffic inputs. VCD
based on specific highways or districts is an example.
Mean statewide or regional traffic inputs. Examples would include ALD for a
certain class of highway.

10

The recommended level of input depends on the significance that the input has on the pavement
design (i.e., the impact of future pavement damage and distress predictions) and the ability to
measure it.
Initial Year Traffic Inputs and Traffic Volume Adjustment Factors
Detailed descriptions of the required traffic inputs are presented in Table 4 through Table 9. An
illustration of the distance from the outer edge of tire to the paint stripe input is shown in Figure
6, of the truck tractor wheelbase input in Figure 7, and various truck input variables in Figure 8.
The column labeled “General Factors that Influence Input” in Tables 4 and 5 provides
information on how the many traffic inputs vary across the highways of Arizona. Although a
factor may influence an input, it does not necessarily indicate that the factor significantly impacts
pavement design.
Summary of MEPDG Traffic Inputs Required
Table 10 presents recommended levels of input for all MEPDG traffic input variables based on
national sensitivity analysis results and engineering experience.

11

Table 4. Initial Year Traffic Data.
MEPDG Traffic Input
Variable
Analysis period or
pavement design life
Date newly
constructed or
rehabilitated and date
pavement is opened
to traffic (each are first
of month specified)

Base year two-way
AADTT

Number of lanes in
design direction

Truck traffic direction
distribution factor, also
referred to as
directional distribution
factor

LDF

Operational speed

Description

Typical Source

Time in years for which the new or
rehabilitated pavement is being designed.
Information used to project future traffic
volumes.
Date on which the new or rehabilitated
pavement is opened for use to public
traffic. Note that the pavement will be
subjected to some form of construction
traffic prior to this date, but this is not
considered.
(a) Total volume of truck traffic (the total
number of heavy vehicles [Classes 4
to 13] in the traffic stream) passing a
point or segment of a road facility to
be designed in both directions during
a 24-hour period.
(b) Determined for the opening to traffic
year.
The number of lanes in the design
direction. Represents the total number of
lanes in one direction
Percentage of all two-way AADTT in the
design lane direction. It is used to
quantify a difference in the overall volume
of trucks in two directions. It is usually
assumed to be 50 percent; however, this
is not always the case as using a different
route for transporting goods to and from
some facilities is quite common.
It is the percentage of trucks in the design
lane as a proportion of all truck traffic in
the design lane direction. For two-lane,
two-way highways (one lane in one
direction), this factor is 1.0 because all
truck traffic in any one direction must use
the same lane.
Truck operational speed or average travel
speed. A description of a detailed
methodology used for determining
operational speeds can be found in the
Transportation Research Board Highway
Capacity Manual or AASHTO’s Policy on
Geometric Design of Highways and
Streets (often referred to as the “Green
Book”).

General Factors that
Influence Input

Obtained from
pavement design
manual

Highway surface type,
functional class

Project specific

Local climate,
contracting policy, traffic
management,
construction type

Obtained from
on-site vehicle
counts data
(AVC, WIM)

Site specific. To obtain
AADTT, the total AADT
and percent of trucks
must be known

Obtained from
geometric design

Traffic volumes,
highway capacity,
congestion

Obtained from
on-site vehicle
counts data
(AVC, WIM) in
both directions

Site specific

Obtained from
on-site vehicle
counts data
(AVC, WIM)

Number of lanes in
design direction,
entrance/exit ramps in
area, AADT

Arizona
Department of
Public Safety and
Police databases

Close to speed limit,
has little effect at higher
speeds, but special
steep grades will greatly
have an effect, as well
as signalized
intersections

AADTT = annual average daily truck traffic; AVC = automatic vehicle classification; LDF = load distribution factor;
other abbreviations and acronyms are as previously defined.

12

Table 5. Truck Traffic Volume Adjustment Factors.
Traffic
Input
Variable

MAF

Vehicle
class
distribution
factors

Truck
hourly
distribution
factors

Description
MAF are used to distribute estimates of annual
truck traffic volumes across the 12 months that
make up a year. Note that although the MEPDG
assumes an even distribution of annual traffic
across 12 months (this implies that the same
number of trucks was applied each month within a
year, default MAF =1.0), in reality, truck volumes
vary across the months. Distribution is performed
separately for each vehicle class or truck type. The
MEPDG assumes that MAF remains stable for the
typical pavement design period.
VCD factors are used to distribute annual truck
traffic volumes across the 10 truck types (FHWA
vehicle Classes 4 through 13) considered by the
MEPDG. The MEPDG assumes that VCD factors
remain stable over the pavement design period.
The MEPDG provides 17default VCD factors called
TTC groups. These default TTC groups
represented different mixes of truck traffic in a
given traffic stream. A detailed definition and
descriptions of the MEPDG TTC groups is
presented in Table 6. VCD factors for each of the
MEPDG default TTC groups is presented in Table
7, while recommendations for assigning TTC
groups based on highway functional class is
presented in Table 8.
Used to distribute estimates of daily truck traffic
volumes across the 24 hours that make up a day.
The MEPDG assumes that truck hourly distribution
factors remains stable over the typical pavement
design period. The MEPDG provides default hourly
truck traffic distribution values.

Source

Factors That
Influence
Input

Obtained
from vehicle
counts data
(AVC, WIM)

Agricultural
and industrial
activities,
seasonal
climatic
effects,
functional
class

Obtained
from vehicle
counts data
(AVC &
WIM)

Agricultural
and industrial
activities,
functional
class, landuse (urban or
rural)

Obtained
from hourly
vehicle
counts data
(AVC, WIM)

Agricultural
and industrial
activities,
functional
class, landuse (urban or
rural), desert
conditions

Used to forecast future truck traffic volumes (over
the design period). For new highways/alignments,
both are estimated using historical truck traffic
Truck
volumes adjusted using trip generation
Obtained
traffic
models/factors. For existing highways/alignments,
from
growth
historical traffic volume counts for the given site is
historical
factors
mostly adequate. Growth type can be none (zero
vehicle
(growth
percent growth), linear, or compound. The rate of
counts data
rate and
truck traffic growth is the average annual percent
(AVC, WIM)
type)
change in truck traffic over the analysis period.
Note that both truck growth rate and type can be
assigned individually for each of the 10 truck
types/vehicle classes considered by the MEPDG.
TTC = truck traffic classification; other abbreviations and acronyms are as previously defined.

13

Economic,
(agricultural,
industrial,
recreational
activities),
climate, landuse (urban or
rural), terrain

Table 5. Truck Traffic Volume Adjustment Factors, continued.
Traffic
Input
Variable

Axles per
truck

Axle load
distribution
(ALD)
factors

Description

Source

Described as the mean number of single, tandem,
tridem, and quad axles per vehicle class/truck type.
It is estimated for each of the 10 truck types/vehicle
classes considered by the MEPDG. It is used to
estimate the total number of single, tandem, tridem,
and quad axles applied at a given site over the
design period.
Used to distribute estimates of single, tandem,
tridem, and quad axles over up to 40 load intervals
for each axle type as follows:
Single axles – 3,000 lb to 40,000 lb at 1,000-lb
intervals.
Tandem axles – 6,000 lb to 80,000 lb at 2,000-lb
intervals.
Tridem and quad axles – 12,000 lb to 102,000 lb
at 3,000-lb intervals.
The MEPDG allows for separate estimates of ALD
factors for the combination of truck type/vehicle
class and month of the year. The MEPDG software
provides default normalized percentage of axle
weights for each vehicle class that falls within each
weight range for each month of the year. Default
values were developed using LTPP traffic data.

14

Obtained
from WIM
site data

Obtained
from WIM
site data

Factors That
Influence
Input
Vehicle
classification,
truck size,
and weight
regulations

Axle type,
vehicle
classification,
truck size,
and weight
regulations;
economic,
(agricultural,
industrial, and
recreational
activities) and
land-use
(urban or
rural)

Table 6. Descriptions of MEPDG Default TTC Groups (ARA, 2004).
Buses in
Traffic Stream

Low to none
(<2%)

Low to
moderate
(>2%)

Major bus
route (>25%)

Commodities Being Transported by Type of Truck
Single-Trailers and SingleMulti-Trailer
Segments
Predominantly single-trailer trucks
High percentage of single-trailer
trucks, but some single-segment
trucks
Relatively high
amount of multi- Mixed truck traffic with a higher
trailer trucks
percentage of single-trailer trucks
(>10%)
Mixed truck traffic with approximately
equal percentages of single-segment
and single-trailer trucks
Predominantly single-segment trucks
Predominantly single-trailer trucks
Mixed truck traffic with a higher
Moderate
percentage of single-trailer trucks
amount of multi- Mixed truck traffic with approximately
trailer trucks (2- equal percentages of single-segment
10%)
and single-trailer trucks

Low to none
(<2%)

Low to none
(<2%)

Predominantly single-segment trucks
Predominantly single-trailer trucks
Predominantly single-trailer trucks, but
with a low percentage of singlesegment trucks
Predominantly single-trailer trucks
with a low to moderate amount of
single-segment trucks
Mixed truck traffic with a higher
percentage of single-trailer trucks
Mixed truck traffic with approximately
equal percentages of single-segment
and single-trailer trucks
Mixed truck traffic with a higher
percentage of single-segment trucks
Predominantly single-segment trucks
Mixed truck traffic with approximately
equal single-segment and singletrailer trucks

15

TTC
Group
No.
5
8
11
13
16
3
7
10
15
1
2

4
6
9
12
14
17

Table 7. Default Vehicle Class Distribution for Each
MEPDG TTC Group (ARA, 2004).
TTC
Group
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

TTC Description
Major single-trailer truck
route (Type I)
Major single-trailer truck
route (Type II)
Major single- and multitrailer truck route (Type I)
Major single-trailer truck
route (Type III)
Major single- and multitrailer truck route (Type II).
Intermediate light and
single-trailer truck route
(Type I)
Major mixed truck route
(Type I)
Major multi-trailer truck
route (Type I)
Intermediate light and
single-trailer truck route
(Type II)
Major mixed truck route
(Type II)
Major multi-trailer truck
route (Type II)
Intermediate light and
single-trailer truck route
(Type III)
Major mixed truck route
(Type III)
Major light truck route
(Type I)
Major light truck route
(Type II)
Major light and multi-trailer
truck route
Major bus route

Vehicle/Truck Class Distribution (percent)
6
7
8
9
10
11
12

4

5

1.3

8.5

2.8

0.3

7.6

74.0

1.2

3.4

0.6

0.3

2.4

14.1

4.5

0.7

7.9

66.3

1.4

2.2

0.3

0.2

0.9

11.6

3.6

0.2

6.7

62.0

4.8

2.6

1.4

6.2

2.4

22.7

5.7

1.4

8.1

55.5

1.7

2.2

0.2

0.4

0.9

14.2

3.5

0.6

6.9

54.0

5.0

2.7

1.2

11.0

2.8

31.0

7.3

0.8

9.3

44.8

2.3

1.0

0.4

0.3

1.0

23.8

4.2

0.5

10.2

42.2

5.8

2.6

1.3

8.4

1.7

19.3

4.6

0.9

6.7

44.8

6.0

2.6

1.6

11.8

3.3

34.0

11.7

1.6

9.9

36.2

1.0

1.8

0.2

0.3

0.8

30.8

6.9

0.1

7.8

37.5

3.7

1.2

4.5

6.7

1.8

24.6

7.6

0.5

5.0

31.3

9.8

0.8

3.3

15.3

3.9

40.8

11.7

1.5

12.2

25.0

2.7

0.6

0.3

1.3

0.8

33.6

6.2

0.1

7.9

26.0

10.5

1.4

3.2

10.3

2.9

56.9

10.4

3.7

9.2

15.3

0.6

0.3

0.4

0.3

1.8

56.5

8.5

1.8

6.2

14.1

5.4

0.0

0.0

5.7

1.3

48.4

10.8

1.9

6.7

13.4

4.3

0.5

0.1

12.6

36.2

14.6

13.4

0.5

14.6

17.8

0.5

0.8

0.1

1.5

16

13

Table 8. Recommendations for Selecting MEPDG TTC Groups Based on
Highway Functional Class (ARA, 2004).
Highway Functional
Class Descriptions
Principal arterials – Interstate and defense
routes
Principal arterials – Intrastate routes, including
freeways and expressways
Minor arterials
Major collectors
Minor collectors
Local routes and streets

Applicable Truck Traffic Classification Group
Number
1,2,3,4,5,8,11,13
1,2,3,4,6,7,8,9,10,11,12,14,16
4,6,8,9,10,11,12,15,16,17
6,9,.12,14,15,17
9,12,14,17
9,12,14,17

Table 9. Truck Traffic Volume Other Adjustment Factors.
Traffic Input
Variable
Mean Wheel
Location (from Lane
Marking) and Truck
Traffic Wander

Truck Wheelbase
Distribution

Axle Configuration

Description

Source

Mean wheel location is the mean distance from
the outer edge of the wheel to the lane
longitudinal pavement marking. Truck traffic
wander is the standard deviation of the
distribution of actual wheel locations (see Figure
6) as a truck travels along the traffic lane.
MEPDG uses a default mean wheel location of
18 inches and a mean truck traffic wander
standard deviation of 10 inches. These values
were used in the national calibration. They
should not be changed without measured data
indicating other values.
Information on mean wheel location and traffic
wander is obtained from actual field
measurements. A review of past literature
indicates very little information available on both
mean wheel location and associated variability.
Default mean wheel location values of 18 inches
and truck traffic wander of 10 inches is provided
by the MEPDG based on information presented
in national literature.
Distance from the steering axle to the first next
axle for trucks Class 8 and above is called the
wheelbase. Three levels are specified as short,
medium, and long. This input affects top-down
cracking of JPCP. Figure 7 illustrates the truck
wheelbase.
Axle configuration inputs required by the MEPDG
are as described in Figure 8.

Past research
national/local
studies. Can be
measured through
use of video
camera, spots on
pavements, etc.

WIM data

Manufacturers’
specifications,
measurements of
individual trucks at
WIM sites, etc.

Factors That
Influence Input
Lane width,
shoulder type, deep
valleys/drop offs,
mountain sides,
etc.

This factor has not
been measured
generally before,
but is affected by
the length of haul of
trucks on the
highway
Legal requirements

JPCP = jointed plain concrete pavement. All other abbreviations and acronyms are as previously defined.

17

Table 9. Truck Traffic Volume Other Adjustment Factors, continued.
Traffic Input
Variable
Tire Pressure

Description

Source

This input is the typical hot rolling tire pressure of
FHWA vehicle Class 4 through 13 trucks. The
MEPDG assumes a default hot tire pressure of
120 psi. The hot inflation pressure is typically
approximately 10 to 15 percent greater than the
cold inflation pressure. A mean tire inflation
pressure of 120 psi was used in the national
calibration and should not be changed without
measured data indicating another value.
Description

Manufacturers’
specifications,
measurements of
individual trucks at
rest areas, etc.

Factors That
Influence Input
Manufacturers’
specifications and
recommendations

Distance from the outer edge of the
wheel to the pavement marking

Figure 6. Example of Distance from the Outer Edge of the Wheel
to the Pavement Marking.

18

Wheelbase

Figure 7. Illustration of Truck Wheelbase Definition.
The percentage of short, medium, and long wheelbase truck tractors is a critical factor in
MEPDG input.

Wheel Base Width

Tire
Pressure
& Loads

Axle
Spacing

Dual Tire
Spacing
Axle Width
Figure 8. Axle Wheel Configuration Inputs (Average Axle Width Edge to Edge),
Dual Tire Spacing, Axle Wheel Spacing (Tandem, Tridem, and Quad Axles).

19

Table 10. Recommended Level of Input for MEPDG Traffic Input Variables.
MEPDG Traffic Input Variable
Analysis period or pavement
design life
Date newly constructed or
rehabilitated and date
pavement is opened to traffic
(each are first of month
specified)
Base year two-way average
initial AADTT
Number of lanes in design
direction
Truck traffic direction
distribution factor, also referred
to as directional distribution
factor

Overall Impact
on Pavement
Design

Level of Effort

Ability to
Measure?

Recommended
Level of Input

High

Low

Yes

Level 1 (site
specific)

Moderate

N/A
(best estimate
based on
construction
expectations)

No

Level 2/3
(estimate only)

High

Moderate

Yes

High

Low

Yes

Low

Moderate

Yes

Level 2/3 (site
specific)

Yes

Level 2/3 (site
specific)

Yes

Level 2/3
(based on
speed limit and
topography)

Yes

Level 2/3
(based on
statewide
defaults)

High (requires an
on-site AVC across
all lanes with an
appropriate
sample)

LDF

Moderate

Operational speed

Low, however if
speed < 30 mph,
can be moderate
to high for HMA

Moderate (requires
an AVC on-site
with an appropriate
sample)

MAF

Low, however
could be moderate
if significant
seasonal
variations exist

High (requires onsite AVC over an
entire year)

Vehicle class distribution
factors

Moderate,
however could be
high if special
recreational or
industrial
conditions exist

Moderate (requires
an on-site AVC
with an appropriate
sample)

Yes

Truck hourly distribution factors

HMA: None
JPCP: Low

Moderate (requires
an on-site AVC
with an appropriate
sample)

Yes

20

Level 1 (site
specific)
Level 1 (site
specific)

Level 1 or 2/3
based on
functional class
(e.g., urban
versus rural,
principal
arterials versus
collectors and
minor arterials)
Level 2/3 based
on functional
class (e.g.,
urban versus
rural, principal
arterials versus
collectors and
minor arterials)

Table 10. Recommended Level of Input for MEPDG Traffic Input Variables, continued.
MEPDG Traffic Input Variable

Overall Impact
on Pavement
Design

Level of Effort

Ability to
Measure?

Recommended
Level of Input

High

Moderate (requires
historical truck
volume data and
expectations of
future land use,
population growth,
etc.)

Low

Moderate (requires
AVC or WIM data
with an appropriate
sample)

Moderate

High (requires WIM
data with an
appropriate
sample)

Yes

HMA: None
JPCP: Moderate
to high

High (requires an
on-site video
measurement
system or manual
observations)

Yes,
pavement
markings
and
observations
from top of
bridge

Level 2/3
(statewide or
national
defaults)

High

High (requires an
on-site video
measurement
system or manual
observations)

Yes, same
as wheel
location

Level 2/3
(statewide or
national
defaults)

Axle spacings

Low

Moderate, WIM
equipment

Yes

Tire pressure

HMA: Moderate
JPCP: Low

High

Yes

Truck wheelbase

HMA: None
JPCP: Moderate

Moderate (requires
WIM)

Yes

Truck traffic growth factors
(growth rate and type)

Axles per truck

ALD factors

Mean wheel location (from
lane marking to outer edge of
wheel)

Truck traffic lateral wander
within lane

21

No, past
growth only

Level 1 (sitespecific
historical traffic
and other data)

Yes

Level 2/3
(statewide or
national
defaults)
Level 2/3 based
on urban versus
rural versus
long desert haul

Level 2/3
(statewide or
national
defaults)
Level 2/3
(statewide or
national
defaults)
Level 2/3
(statewide or
national
defaults)

22

CHAPTER 3. FRAMEWORK FOR DEVELOPING THE ADOT MEPDG
TRAFFIC DATA INPUT SYSTEM
The framework for developing the ADOT MEPDG traffic data input system is presented below:
1. Traffic data identification and assembly.
2. Traffic data processing, review, identification of anomalies and errors, and data cleansing.
3. Statistical analysis to assign measured traffic data into subsets or natural groupings
(called clusters) with similar characteristics and distribution patterns.
4. Determination of optimum number of clusters within Arizona for each of the following
MEPDG traffic data types:
a. MAF.
b. Hourly truck distribution.
c. VCD (for a given highway section, VCD affects the computation of the number of
single, tandem, tridem, and quad axles that pass over the design period and is thus
an important MEPDG input).
d. ALD factors.
e. Number of axles per truck.
5. Performance of sensitivity analysis and interpretation of sensitivity analysis results.
6. Development of default statewide Level 2/3 traffic inputs for the MEPDG
implementation in Arizona.
The following sections describe these steps in greater detail.
STEP 1: TRAFFIC DATA IDENTIFICATION AND ASSEMBLY
Several government entities monitor and collect traffic data in Arizona, leading to significant
variations in traffic data collection practices, data accuracy, and data storage practices and
availability. For the SPR-672 study, a comprehensive effort was required to identify the historic
traffic data available in Arizona.
A thorough review of ADOT and other state entities’ business practices identified at least three
entities that could potentially supply the traffic data required for this study:
ADOT Motor Vehicle Division (MVD).
ADOT Multimodal Planning Division (MPD).
ADOT Arizona Transportation Research Center (ATRC).
The researchers made an initial effort to obtain Arizona traffic data and review the data for
usefulness. AVC data collected at various sites across the state were obtained from the MVD.
Data from 10 WIM sites and eight AVC sites across the state were available from the ADOT
Research Center through the FHWA LTPP program. Although the MPD collects WIM data at
port-of-entry (POE) sites across the state, efforts to obtain these data were not successful.
All of the data obtained were assembled in a project database. The following sections provide
detailed descriptions of the data assembled.

23

Summary of Data Assembled from the MVD
From the MVD, the researchers obtained VCD data from 21 sites across the state. Data obtained
from all of the sites applied the FHWA 13-bin classification scheme. Table 11 presents general
information and characteristics of the sites from which VCD data were available. Figure 9
presents a map showing the locations of the 21 automated traffic recorder (ATR) sites,
illustrating the statewide coverage of the representative ATR sites.
Table 11. Arizona ATR Sites Used in the Analysis of VCD.

Site

Lanes

County

Route

Functional Class

Latitude

Longitude

100010
100070

4
4

Yuma
La Paz

I-08
I-10

32.6780
33.6610

-114.0380
-114.0060

100139

6

Pima

I-10

32.4540

-111.2050

100188
100327

4
4

Cochise
Mohave

I-10
I-15

32.3410
36.9800

-109.5680
-113.6540

100473

4

Pima

I-19

32.1710

-110.9850

100537

4

Coconino

I-40

35.2300

-111.8100

100541

4

Coconino

I-40

35.1730

-111.6470

100767
100800
100854
100922
101113

2
6
2
4
2

La Paz
Pima
Pinal
Maricopa
Yuma

SR 72
SR 77
SR 79
SR 85
SR 95

33.8530
32.3430
33.1550
33.2630
33.7580

-113.9070
-110.9770
-111.3560
-112.6340
-114.2170

101248

10

Maricopa

SR 101

33.4570

-111.8900

101602

2

Maricopa

SR 303

33.6360

-112.4180

101622
101849
101928
102068
102094

4
4
2
4
2

Pinal
Maricopa
Navajo
Coconino
Yavapai

33.0920
33.6890
34.2090
35.2590
34.0120

-112.0340
-112.4150
-110.0780
-111.5510
-112.7890

102230

2

Graham

SR 347
U.S. 60
U.S. 60
U.S. 89
U.S. 93
U.S.
191

Rural Principal Arterial - Interstate
Rural Principal Arterial - Interstate
Urban Principal Arterial Interstate
Rural Principal Arterial - Interstate
Rural Principal Arterial - Interstate
Urban Principal Arterial Interstate
Rural Principal Arterial - Interstate
Urban Principal Arterial Interstate
Rural Major Collector
Urban Principal Arterial - Other
Rural Minor Arterial
Rural Principal Arterial - Other
Rural Principal Arterial - Other
Urban Principal Arterial - Other
Freeways or Expressways
Urban Principal Arterial - Other
Freeways or Expressways
Rural Minor Collector
Rural Principal Arterial - Other
Rural Minor Arterial
Urban Principal Arterial - Other
Rural Principal Arterial - Other
Rural Major Collector

32.7960

-109.5400

24

Figure 9. Locations of the Arizona ATR Data Collection Sites.
Summary of Data Assembled from the LTPP Regional Center
The LTPP Western Regional Center collects WIM and AVC data in two Canadian provinces and
12 states in the United States, including Arizona. The LTPP program uses the raw AVC and
WIM data to compute several of the parameters that are required MEPDG traffic inputs.
For this study, various MEPDG computed traffic inputs were estimated using raw data from 10
Regional Center WIM sites and eight Regional Center AVC sites. The data were obtained from
the LTPP traffic and inventory databases (Standard Data Release 23.0, January 2009). Table 12
lists the LTPP data tables from which traffic and related data were obtained.

25

Table 12. LTPP Data Tables from Which Data Were Obtained for Analysis.
LTPP Data Table

TRF_MEPDG_MONTH_ADJ_FACTR

TRF_MEPDG_HOURLY_DIST

TRF_MEPDG_AX_DIST_ANL

TRF_MEPDG_AX_PER_TRUCK

TRF_MEPDG_VEH_CLASS_DIST

INV_ID

Description
This table contains adjustment factors for ADTT for each truck
class by month based on either classification or weight monitoring
data as indicated by the code contained in the TRF_DATA_TYPE
field. A value of four in the TRF_DATA_TYPE field indicates the
estimate was based on only classification data, and a value of
seven indicates the estimate was based on only weight data.
This table contains annual average hourly distribution of trucks by
hour in the LTPP lane based on classification data. The
computations were performed following the algorithm contained in
the MEPDG developed under NCHRP project 1-37A. The table
contains data from only SPS_1, -2, -5 and -6 sites, which have
passed a validation study under the SPS WIM Pooled Fund study.
Only years with at least 210 days of classification data are
included.
This table contains normalized axle distributions by month, truck
class, and axle group. Records in this table are generated from the
MM_AX table in the LTPP traffic database that contain at least 210
days of WIM data in that calendar year. The monthly distribution
bin counts are based on day of the week averages. The 4,000-lb
weight bins for quad axles in the LTPP traffic database are
reduced to the MEPDG 3,000-lb weight bins using an assumption
that the 4,000-lb bins have a uniform distribution between adjacent
bins.
This table contains the annual average number of number of axles
by vehicle class and axle type by year. This is computed from the
axles actually weighed as summed in the
TRF_MONITOR_LTPP_LN table. In this beta release of data,
records with average numbers of axles per truck less than 0.1 or
greater than five have a RECORD_STATUS=C.
This table contains the percentage of trucks by vehicle class within
the truck population (FHWA Classes 4 through 13) in the LTPP
lane-based classification, weight, or a combination of classification
and weight data as indicated by the code contained in the
TRF_DATA_TYPE field. For some sections, up to three different
estimates are provided. Estimates are provided by year. On SPS
sites, the estimates are provided using a project-level Strategic
Highway Research Program (SHRP) ID. In most cases, it is a good
assumption that the project level traffic applies to all test sections
on the project. The SPS_PROJECT_STATIONS table can be used
to identify sites where test sections are located in both directions of
travel on one SPS project.
This table contains section location coordinates by route number
and milepost, longitude and latitude, direction of travel,
identification if the location is part of the FHWA Highway
Performance Monitoring System, and county/parish name.
Location information is provided in this table for sections classified
in a GPS experiment or an SPS maintenance and rehabilitation
experiment where CONSTRUCTION_NO = 1 in the
EXPERIMENT_SECTION table. Location information for SPS
projects that is based on construction of a new pavement structure
is stored in the SPS_ID table.

NCHRP = National Cooperative Highway Research Program; SPS = Specific Pavement Studies; GPS = General
Pavement Studies; all other abbreviations and acronyms are as previously defined.

26

General information and characteristics of the LTPP sites with MEPDG traffic data available are
presented in Table 13. A map showing the locations of the 32 LTPP projects is presented in
Figure 10, which illustrates the statewide coverage of the representative LTPP sites. Two sets of
LTPP pavement sites—0100, 0900, and A900 located on U.S. 93; and 1007 and B900 located on
I-10—were so geographically close to each other that traffic data from these project sites were
deemed the same.

Figure 10. LTPP Sites across Arizona.

27

Table 13. Detailed Description of LTPP Sites in Arizona.
No.

SHRP
ID

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32

0100
0200
0500
0600
0900
1001
1002
1003
1006
1007
1015
1016
1017
1018
1021
1022
1024
1025
1034
1036
1037
1062
1065
6053
6054
6055
6060
7079
7613
7614
A900
B900

Total
Lanes
(TwoWay)

4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
2
4
2
4
4
4
4
2
4
6
6
6
4
4

Pavement Type

County

FHWA
Functional
Class*

Travel
Direction

Milepost

Route No.

HMA
PCC
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA
HMA over HMA
HMA over HMA
HMA over HMA
HMA over HMA
CRCP
JPCP
JPCP
HMA
HMA

Mohave
Maricopa
Pinal
Coconino
Mohave
Maricopa
Yavapai
Maricopa
Maricopa
Maricopa
Santa Cruz
Santa Cruz
Pima
Pima
Mohave
Mohave
Yavapai
Yavapai
La Paz
Mohave
Mohave
Mohave
Yavapai
Pima
Santa Cruz
Maricopa
Santa Cruz
Maricopa
Maricopa
Maricopa
Mohave
Maricopa

RPA - US
RPA - I
RPA - I
RPA - I
RPA - US
RPA - I
RPA - I
RPA - I
RPA - I
RPA - I
RPA - I
RPA - I
RPA - I
RPA - I
RPA - I
RPA - I
RPA - I
RPA - I
RMA
RPA - US
RPA - SR
RPA - I
RPA - I
RPA - I
RPA - I
PRA - SR
RPA - I
UPA – O
UPA – SR
RPA – I
RPA - US
RPA - I

Northbound
Eastbound
Eastbound
Eastbound
Northbound
Westbound
Westbound
Westbound
Westbound
Westbound
Southbound
Southbound
Northbound
Southbound
Westbound
Westbound
Eastbound
Westbound
Southbound
Northbound
Eastbound
Westbound
Eastbound
Eastbound
Southbound
Southbound
Northbound
Northbound
Westbound
Westbound
Northbound
Westbound

52.62
109
159.01
202.16
60.14
123.34
145.37
98.53
110.65
115.43
18.33
24.17
32.98
36.2
72.87
77.69
106.95
113.03
145.25
27.64
1.4
92.75
97.72
292.89
52.25
141.84
14.88
11.9
180
130.5
60.14
122.29

U.S. 93
I-10
I-8
I-40
U.S. 93
I-10
I-40
I-10
I-10
I-10
I-19
I-19
I-19
I-19
I-40
I-40
I-40
I-40
SR 95
U.S. 93
SR 68
I-40
I-40
I-10
I-19
SR 85
I-19
101
SR 360
I-10
U.S. 93
I-10

RPA-I: Rural Principal Arterial-Interstate; RLC: Rural Local Collector; RPA-US: Rural Principal Arterial-US Route; RMA: Rural Minor
Arterial; RMC: Rural Major Collector; UPA-State: Urban Principal Arterial-State Route; UPA-US: Urban Principal Arterial-US Route; CRCP =
continuously reinforced concrete pavement; HMA = hot mixed asphalt.

28

STEP 2: TRAFFIC DATA PROCESSING, REVIEW, IDENTIFICATION OF
ANOMALIES AND ERROR, AND DATA CLEANSING
The reviewers performed step 2 based on published recommendations for reviewing traffic data
(AASHTO, 2009; FHWA, 2009) as well as engineering judgment.
Data Processing
Data processing consisted of the following:
MVD raw AVC and WIM data:
o Raw data in electronic format were collected by the MVD. The raw data were
processed using ADOT-licensed TRADAS software to create Traffic Monitoring
Guide classification (C-card) and weight (W-card) files (FHWA, 2001).
o The MVD provided the Traffic Monitoring Guide C-card and W-card files to the
researchers.
o The C-card and W-card files were processed using ARA’s Advanced Traffic
Loading and Analysis System (ATLAS) software. The essential features of
ATLAS that were used for data processing were:
 Traffic import module that was used to process and read the Traffic
Monitoring Guide C-card and W-card data.
 Traffic export module that was used to create site-specific MEPDG traffic
input files (vehicle classification, ALD, MAF, 24-hour truck counts, and
growth rates based on historical data), a reference library database, and
ESAL estimates.
 Data analysis module to perform quality checks on the historical traffic
data and perform data filtering on a site-by-site basis and by truck class.
o Outputs from the ATLAS software was assembled in a project database for
further review and consisted of the following data types for each site analyzed:
 AADTT (by site, direction, lane number, year, and vehicle class).
 Hourly truck distribution (by site, direction, and lane number).
 Hourly truck volume (by site, direction, lane number, year, month, day,
and week).
 VCD (by site, direction, lane number, year, and month).
 Wheelbase of truck Classes 8 through 13 was determined from two
Arizona LTPP WIM sites. The results obtained for short, medium, and
long truck wheelbases were very similar from site to site; however,
additional data are desirable to provide a more accurate estimate. The
results are summarized in Table 14.

29

Table 14. Arizona Truck Wheelbase Distribution at Two Sites
(Classes 8 through 13 Only).
Wheelbase Type
Short
Medium
Long

Wheelbase Length (feet)
10.0 to 13.4
13.5 to 16.5
16.6 to 20.0

Percent of Trucks
(Classes 8 through 13)
11
17
72

Field measurements:
o ARA staff collected data on lateral wander (within a traffic lane) of trucks. This
was done by making small marks at 6-inch spacings across the outer wheel path
near an overhead bridge. Observations of the lateral offset of the outer edge of the
truck/tire from the paint strip were made from the bridge. Data were obtained
from four sites for a significant number of trucks. The mean and standard
deviation of truck wander was computed and combined from all four sites.
Regional Center LTPP data:
o LTPP traffic data were received post-processing. The LTPP data received did not
contain “raw” traffic data measurements (counts, weights, classification, etc.), but
rather estimates of various MEPDG traffic input variables computed from the
LTPP AVC and WIM sites in Arizona. (If required, the raw data can be obtained
directly from LTPP.) Also, as part of the data processing, the LTPP data received
various levels of quality assurance checks to ensure accuracy and reasonableness.
The processed MVD and LTPP traffic data were used to compute required MEPDG traffic inputs
and put in a database for further review, identification of anomalies and error, and cleansing.
Data Review
The MVD and LTPP traffic data were subjected to rigorous quality control checks. Review and
identification of anomalies consisted of:
Developing plots for use in accessing reasonableness of data and trends in data over the
years:
o Plot of percent truck versus hour of the day (midnight through 11:00 pm) for all
years with data available for a given site.
o Plot of MAF versus month of the year (January through December) for all years
with data available for a given site.
o Plot of percent of trucks versus vehicle class (Classes 4 through 13) for all years
with data available for a given site.
o Plot of number of single, tandem, tridem, and quad axles per truck versus vehicle
class (Classes 4 through 13) for all years with data available for a given site.
o Plot of percent single, tandem, tridem, and quad trucks versus axle load (e.g., for
single axles 3,000 lb to 41,000 lb in 1,000-lb increments) for all years with data
available for a given site.

30

Review of the plots for consistency, accuracy, and completeness (note that this did not
involve basic quality assurance/quality control checks of the raw traffic data, but rather a
check of MEPDG computed traffic inputs). Examples of the checks that were performed
are as follows:
o Whether hourly truck distribution factors add up to 100 percent or if the MAFs
add up to 12.
o Occurrences of long zero or “flat” periods in the monthly adjustment or hourly
distribution data (several months or hours with no data).
o Whether plots of axle loads versus the percentage of all axles display distinct
peaks as expected, and whether the percentage of all axles of a given axle type
add up to 100.
o Was there consistency in trends over the years with data?
Identification of Anomalies and Error
The plots developed for each site with data were reviewed and checked for reasonableness and
consistency. Also, basic statistics such as mean, standard deviation, variance, etc., were
computed to identify outliers and potential errors.
Data points and overall trends found to be inconsistent with expected trends were flagged. A
tremendous effort was made during review to distinguish between unusual data, correct data, and
incorrect data. For example, both breakdown in equipment and a special event could cause
significant changes in expected traffic patterns. Generally, such data were identified and
removed from the database, as the specific cause of the unusual data pattern was not important.
Other causes of unusual traffic patterns were construction of new freeways in the Phoenix area
that may have resulted in significant change in VCD and the stoppage of heavy trucks from using
U.S. 93 since September 2001, resulting in significant change in VCD after 2001 on that
highway (see Figures 11 and 12). Plots of all of the key MEPDG inputs for all sites with traffic
data assembled are presented in Appendixes B through F. Examples of the plots used in data
review and identification of anomalies are presented in Figures 11 through 17.

31

SectionID=4_0100
100

Percentage of Trucks

90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1994
1998

1995
1999

1996
2000

Figure 11. Plot of Vehicle Class Distribution for Site 4_0100
(Prior to September 2001).
SectionID=4_0100_R

Percentage of Trucks

100
90

U

80
70
60
50
40
30
20

U

10
0

U
4

5

U

U

6

7

U
8

9

U

U

U

U

10

11

12

13

Vehicle Class
YEAR

1994
1999
2005

1995
2000
U U U 2006

1996
2001
2007

1997
2003
2008

1998
2004
2009

Figure 12. Plot of Vehicle Class Distribution for Site 4_0100 (Prior to and After September
2001) Showing Significant Reduction in Class 9 Trucks.

32

SectionID=4_100070

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure 13. Plot of Hourly Truck Distribution for Site 4 100070.
3.0

1994
2.5

1995
1996
1998
1999

1.5

2000
1.0

2005
2007

0.5

Dec

Nov

Oct

Sep

Aug

Jul

Jun

May

Apr

Mar

Feb

0.0

Jan

MAF

2.0

Month

Figure 14. Plot of Monthly Adjustment Factors for LTPP 0100
(Class 4 Vehicles Only).

33

100

90

% Trucks

80
70

1994

60

1996
1998

50

2000

40

2005

30

2007

20
10
0

4

5

6

7

8

9

10

11

12

13

FHWA Vehicle Class

Figure 15. Plot of Vehicle Class Distribution for LTPP 1001.

6.0

Axles/Truck

5.0

4.0

2004
2005

3.0

2006
2007

2.0

1.0
0.0

4

5

6

7

8

9

10

11

12

13

FHWA Vehicle Class

Figure 16. Plot Showing Number of Single Axles Per Truck for LTPP 0500.

34

SectionID=4_1001 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

1994

1995

Figure 17. Plot Showing Tandem-Axle Load Distribution for LTPP 1001.
Data Cleansing
The outcome of the data review process was the identification of all potentially anomalous or
erroneous data. All suspected anomalous or erroneous data were removed from the project
database and not used in the analysis. Table 15 lists the sites from which all reasonably good and
accurate hourly distribution, MAFs, VCD, axles per truck, and ALD data were obtained. Note
that only traffic data from the design lane (for highways with multiple lanes) were assembled for
use in this analysis.

35

Table 15. Summary of Traffic Data Availability for Analysis in Arizona.
SHRP ID
100010
100070
100139
100188
100327
100473
100537
100541
100767
100800
100854
100922
101113
101248
101602
101622
101849
101928
102068
102084
102094
102230
0100
0200
0500
0600
0900
1001
1002
1003
1006
1007

Lane
Number
1
2
2
1
1
2
2
2
1
3
1
1
1
4
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

North

East
X
X
X
X

X
X

Direction
South

West
X
X
X
X

X
X
X
X
X

X
X
X
X
X
X
X

X
X
X
X
X
X
X
X
X
X

X
X
X
X
X
X
X

X
X
X
X
X
X

X
X
X
X
X
X
X
X
X

36

Table 15. Summary of Traffic Data Availability for Analysis in Arizona, continued.
SHRP ID
1015
1016
1017
1018
1021
1022
1024
1025
1034
1036
1037
1062
1065
6053
6054
6055
6060
7079
7613
7614
A900
B900

Lane
Number
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

North

East

Direction
South
X
X

West

X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X

STEP 3: STATISTICAL ANALYSIS TO ASSIGN MEASURED TRAFFIC DATA INTO
CLUSTERS WITH SIMILAR CHARACTERISTICS AND DISTRIBUTION PATTERNS
The main objective of this traffic data analysis was to:
Determine how representative the available traffic data are for pavement design in
Arizona using the MEPDG.
Detect natural groupings or clusters within the available traffic data.
Develop defaults for Level 2/3 MEPDG traffic inputs for pavement design.
Develop recommendations regarding traffic data collection practices and uses for
pavement design in Arizona.
Satisfying the project objectives required performing statistical analysis to determine natural
clusters within the traffic data, as well as the optimum number of clusters.
The researchers determined the natural clusters within the assembled data using statistical
multivariate hierarchical cluster analysis. Multivariate hierarchical cluster analysis is a statistical
procedure used to group “like” observations together when the underlying structure of the data is
unknown. Hierarchical cluster analysis consists of a series of successive divisions of the
assembled traffic dataset, which for analysis, considered a single cluster or a merger of data from
individual sites to form a single cluster. The divisions or mergers are performed according to
their similarities in the individual datasets. The similarities are based on distances between

37

individual datasets of clusters within the larger database. Thus, cluster analysis begins with
grouping individual sites with the smallest distances between them to form the first set of
clusters. Next, the individual sites with the next smallest distances between them and the clusters
are added to the original set of clusters. This continues until all individual observations and
clusters end up together in one large group. Although clusters can be developed using a variety
of different methods, all of the methods available apply some measure of distance between
observations as a basis for creating clusters.
Since the cluster analysis methodology does not require prior knowledge of the number of
clusters within a given set of data, it is critical that a procedure be applied to determine, in an
efficient manner, the optimum number of clusters within the database being analyzed. There is
no clean-cut method for determining the optimum number of clusters within a dataset. Analysts
must depend on a combination of diagnostic statistics to determine the optimum number of
clusters. Although several of these statistics are available, for this study, the following five
diagnostic statistics were selected for use in determining an optimum number of clusters:
Cubic clustering criterion (CCC).
Cumulative and partial squared multiple correlations (R2).
Eigenvalue and associated variance (VAR).
Pseudo F (PSF).
Pseudo t2 (PST2).
Criteria for selecting the optimum number of clusters based on these five statistics are
summarized in Table 16.

38

Table 16. Criteria for Selecting the Optimum Number of Clusters.
Statistic

CCC

R2

VAR

PSF

PST2

Criteria
Evaluate plot of CCC versus number of clusters. Local
peaks indicate potential optimum number of clusters. If
the local peak occurs when the value of the CCC is
greater than 2 or 3, it is a good indication that the
corresponding number of clusters is most likely the
optimum. Local peaks occurring at CCC values between
zero and two indicate potential clusters, however, they
should be considered with caution while large negative
values can indicate outliers.
Evaluate plot of R2 versus number of clusters. As R2 is
an indicator of the proportion of variance accounted for
by the clusters, typically, the optimum number of
clusters must account for a significant proportion of
variance in that raw data. Optimum number of clusters
when the addition of the next additional cluster does not
significantly change R2 (e.g., increase in R2 is less than
five percent).
The number of clusters is determined based on the
following:
VAR is greater than 1.0
Proportion of variance for each cluster is greater
than 5 percent
Cumulative proportion of variance is greater than 70
percent
Relatively large local peak values of this statistic
generally indicate a potential optimum number of
clusters. For most analysis, there are several
local/global maximums (peaks) of the PSF statistic. In
such situations, the appropriate value is the number of
clusters value that corresponds to results from other
statistics such as CCC.
A general rule for interpreting the values of PST2 is to
evaluate the plot of t2 versus the number of clusters
(moving from right to left, decreasing the number of
clusters). Identify all PST2 values markedly lager than
the previous value. Move back one cluster (increasing)
and this is a potential optimum number of clusters for
the data being analyzed. For most analysis, there are
several local/global maximums (peaks) of the PST2
statistic. In such situations, the appropriate value is the
number of clusters value that corresponds to results
from other statistics such as CCC.

39

Source

Adapted after
SAS, 1999;
Fernandez, 2003;
Khattree and
Naik, 2000

Adapted after
SAS, 1999

Adapted after
SAS, 1999;
Fernandez, 2003;
Khattree and
Naik, 2000

Adapted after
SAS, 1999;
Fernandez, 2003;
Khattree and
Naik, 2000

STEP 4: DETERMINATION OF OPTIMUM NUMBER OF CLUSTERS WITHIN
ARIZONA
CCC, R2, VAR, PSF, and PST2 were used as needed in determining the optimum number of
clusters for each traffic data type. As noted, since no one method was more accurate than the
others, a consensus determination of the optimum number of clusters was developed based on
the results from all of the statistics. A visual dendogram (a graphical representation of the
clustering procedure as a hierarchical tree, where each step in the clustering process is illustrated
by the joining of the tree) was produced and reviewed to confirm the results of the diagnostic
statistics. Where no useful results were produced by the diagnostic statistics, an optimum number
of clusters was determined by reviewing the dendogram plot alone. The optimum number of
clusters for Arizona traffic data was determined for each key MEPDG traffic input individually,
including:
MAF.
Hourly distribution.
VCD (for a given highway section, VCD affects the computation of the number of single,
tandem, tridem, and quad axles that pass over the design period and is thus an important
MEPDG input).
ALD factors.
Number of axles per truck.
For this study, the Cluster and Aceclus procedures in the SAS statistical package were used for
all analyses (SAS, 1999).
STEP 5: PERFORMANCE OF SENSITIVITY ANALYSIS AND INTERPRETATION OF
SENSITIVITY ANALYSIS RESULTS
As noted, statistical cluster analysis groups data in natural clusters with similar characteristics.
However, although the VCD from the various sites in Arizona representing different highway
functional classes (e.g., urban Interstate versus rural minor arterial), geographic locations (south
versus north), and population centers (rural versus urban) may be grouped into various
combinations of clusters, the effect of the typical VCD on actual pavement design may not be
significant (e.g., < 0.5 in difference in design pavement thickness). Therefore, it is necessary to
conduct a comprehensive sensitivity analysis using typical ADOT new HMA pavement and new
JPCP to determine:
If there are significant differences in pavement design due to the various clusters
identified in step 4.
Whether and how clusters that do not produce significantly different designs can be
combined as needed.

40

STEP 6: DEVELOPMENT OF DEFAULT STATEWIDE LEVEL 2/3 TRAFFIC INPUTS
The MEPDG requires several traffic data inputs, as described in Chapter 2. The required inputs
are mostly obtained from a mix of traffic data monitoring and collection equipment (WIM, AVC,
and Arizona research sites). In practice, for a given design project, traffic data are synthesized by
combining data from many sources. The sources can be site-specific or statewide/regional or
national in nature.
The following levels of traffic data input are defined for Arizona and have been simplified from
the initial MEPDG definitions. The level of input depends on the source of the data, as follows:
Level 1: Traffic data inputs are measured on or near the highway segment location.
Traffic data measured at the site include vehicle counts, vehicle classification, truck lane
percentage, monthly truck distribution, hourly truck distribution, and other inputs. These
should be measured by lane and direction over a sufficiently long period of time to
reliably establish patterns in these traffic inputs. It is possible only with an on-site WIM
installation, and it is recommended for use in designing most high-volume highways.
Level 2/3: Traffic data inputs are obtained from correlation or association with
other traffic or other factors, or from averages of volume, growth, vehicle
classification, axle weight data, hourly truck percentages, and other inputs. For
example, some traffic inputs are directly related to functional classification of the
highway, including VCD. Lane truck distribution is estimated using number of lanes and
truck volume. These traffic data should be obtained from AVC and/or WIM installations
from sites that exhibit similar traffic distributions and load patterns as the site in question.
Level 2 and Level 3 require some sort of regional or national default inputs for vehicle
classification and/or ALD.
The primary objective of this study was to develop default Level 2/3 MEPDG traffic inputs for
pavement design in Arizona. This was accomplished by synthesizing information and analysis
outcomes resulting from steps 1 through 5 as follows:
1. Determine optimum number of natural clusters from the various project sites (AVC and
WIM data) within Arizona for the following traffic inputs:
a. MAF.
b. Hourly distribution.
c. VCD.
d. ALD factors.
e. Number of axles per truck.
Note that, for monthly distribution, axles per truck, and ALD, the optimum number of
clusters was determined using data from only the predominant vehicle classes (Classes 5
and 9, which accounted for more than 70 percent of all trucks).
2. For each of the five traffic inputs listed above, develop a detailed description of the
site/traffic characteristics (functional class, location, predominant truck types, etc.) of
each of the clusters identified.

41

3. For each of the five traffic inputs, compare each cluster identified to the MEPDG defaults
(e.g., for VCD, MEPDG defaults are TTC groupings 1 through 17) and determine if they
are very different from the national defaults.
4. Use the results of the sensitivity analysis to revise the optimum number of clusters.
5. For each of the five traffic inputs, develop default MEPDG inputs and recommendations
for assigning default inputs based on the sensitivity analysis and revised optimum number
of clusters. Note that the MEPDG default inputs are basically mean values for all sites
that fall into a given cluster category.

42

CHAPTER 4. STATISTICAL CLUSTER ANALYSIS
The results of the statistical cluster analysis for the key MEPDG traffic inputs are presented in
this chapter.
VEHICLE CLASS DISTRIBUTION
Analysis of VCD Using ADOT Sites Only
Data were evaluated from the 21 AVC sites to help derive Level 2/3 defaults for MEPDG traffic
inputs. The MEPDG includes TTCs that include national recommendations or defaults (based on
averages from over 100 sites located across the United States) for 13-bin vehicle classes. How
well do these TTC VCDs match Arizona traffic? Based on this information, Arizona-specific
TTCs can be derived as needed. The TTCs are based on functional class and a description of the
truck mix. The initial step was to determine what MEPDG TTCs reasonably represent Arizona
highways.
A significant challenge was presented by the presence of one of the most prevalent vehicles on
Arizona roads—recreational vehicles. Although these vehicles do not have a significant impact
on MEPDG pavement design when classified correctly, the cross-classifications of recreational
vehicles between vehicle Classes 4, 5, 6 and 8 creates a disproportionate distribution of the types
of vehicles. Recreational vehicles pulling two-axle trailers, or other Type 5 or Type 3 vehicles
pulling campers, often are classified as Class 8 vehicles, which play a much more significant role
in MEPDG design. For the Arizona AVC data that were analyzed, 60 percent of the vehicles
were classified as Class 4, 5, 6, or 8. For current and future AVC installations, it is recommended
that a manual classification study be performed to verify the accuracy of the classification
algorithm being used by the data collection equipment.
In developing Arizona highway TTCs, significant emphasis was placed on the percentage of
Class 9 trucks, which are typically classified correctly, barring any equipment problems.
However, Class 5 percentages were also considered. In addition, the presence of one (usually
Class 9) or two humps (Classes 5 and 9) in the distribution curves was considered.
For comparative purposes, the national MEPDG TTC classification distributions are shown in
Table 17. The numbers of representative Arizona sections that follow these distributions
relatively closely are shown in Table 18.

43

Table 17. National Highway TTC VCD Defaults in the MEPDG.

TTC
1
2
3
6
9
12
14

Arizona
Representative
Highways
Included
11
18
7
12
6
24

Percentage of All Trucks
VC4

VC5

VC6

VC7

VC8

VC9

VC10

VC11

VC12

VC13

1.3
2.4
0.9
2.8
3.3
3.9
2.9

8.5
14.1
11.6
31.0
34.0
40.8
56.9

2.8
4.5
3.6
7.3
11.7
11.7
10.4

0.3
0.7
0.2
0.8
1.6
1.5
3.7

7.6
7.9
6.7
9.3
9.9
12.2
9.2

74.0
66.3
62.0
44.8
36.2
25.0
15.3

1.2
1.4
4.8
2.3
1.0
2.7
0.6

3.4
2.2
2.6
1.0
1.8
0.6
0.3

0.6
0.3
1.4
0.4
0.2
0.3
0.4

0.3
0.2
6.2
0.3
0.3
1.3
0.3

Table 18. VCD TTCs Based on Arizona Data That Are Closely Related
to the National TTCs.
Arizona
Derived
TTC
1
2
6
9
12
14

Percentage of All Trucks
VC4

VC5

VC6

VC7

VC8

VC9

VC10

VC11

VC12

VC13

1.8
3.1
3.7
5.3
5.3
7.8

6.5
14.7
21.3
38.5
46.3
65.8

1.9
2.9
5.7
6.2
5.7
4.4

0.2
0.1
0.4
0.2
0.7
0.2

10.3
9.3
19.0
9.0
16.1
11.7

73.2
64.4
45.6
36.9
24.1
9.1

1.0
1.3
1.7
1.8
1.1
0.7

3.1
1.9
1.5
1.3
0.3
0.2

1.9
1.5
0.7
0.3
0.1
0.0

0.1
0.8
0.4
0.4
0.3
0.1

Classification data from 21 Arizona AVC segments were analyzed to develop clusters for Level
2/3 Arizona TTC development. These data provided 84 lanes of statistics for analysis. There
were seven national TTCs represented by Arizona highways. The vehicle classification
distributions for the representative lanes evaluated are presented in Appendix B.
Once representative Arizona vehicle classification distributions were developed from Arizona
AVC data, they were compared with the national MEPDG defaults in the MEPDG software. The
comparisons are presented in Table 19. For example, a Class 9 vehicle for TTC 1 in the MEPDG
is 74 percent. A Class 9 vehicle for the TTCs derived for Arizona is 73.2 percent. The difference
is 74 – 73.2 = 0.8 percent, as shown in Table 19.
From the table, it can be seen that the greatest discrepancy in distributions is among Class 5, 6,
and 8 vehicles. This is mainly due to the cross-classification problems described earlier in this
report. As stated, the percentage of Class 9 vehicles was the primary consideration in
determining TTCs for Arizona. There are no major differences between the Level 3 MEPDG
defaults and the Arizona truck distribution.

44

Table 19. Differences between MEPDG and Arizona TTC Recommendations for VCD.
TTC
1
2
6
9
12
14

VC4
0.5
0.7
0.9
2.0
0.5
4.9

VC5
-2.0
0.6
-9.7
4.5
7.9
6.6

VC6
-0.9
-1.6
-1.6
-5.5
-8.1
-5.4

VC7
-0.1
-0.6
-0.4
-1.4
-1.4
-3.3

Percentage of All Trucks
VC8
VC9
VC10
2.7
-0.8
-0.2
1.4
-1.9
-0.1
9.7
0.8
-0.6
-0.9
0.7
0.8
2.5
2.2
-2.0
3.2
-5.7
0.3

VC11
-0.3
-0.3
0.5
-0.5
-0.3
-0.1

VC12
1.3
1.2
0.3
0.1
-0.1
-0.4

VC13
-0.2
0.6
0.1
0.1
-1.2
-0.2

Considerable time was spent examining the actual VCDs. The distributions divide into two major
groups:
Single peak Class 9 vehicles, as shown in Figure 18. This distribution is typical of
Arizona Interstate highways in rural and urban areas. However, a few of these urban sites
show double peaks.
Double peak Class 5 and 9 vehicles as shown in Figure 19. This distribution is typical of
all other functional classes, in particular urban sites.
Table 20 shows a possible Level 3 selection criterion for inputting MEPDG TTCs based on
highway functional class. Arizona Interstates are represented primarily by TTCs 1, 2, and 3. This
indicates that the classification distribution on these roads consists primarily of Class 5 and 9
vehicles. There are also a significant number of Class 8 vehicles, which may be a combination of
semi-tractor trailers and recreational vehicles. Other arterial roadways, such as urban and rural
roadways, also show Class 5 and 9 vehicle peaks; however, the number of Class 5 vehicles is
greater on these roads than on Interstates. All other roadways are primarily represented by a
mixture of Class 5 and 9 vehicles.
SectionID=4_1001_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20

U

10
0

U
4

5

U
6

U
7

U
8

U
9

10

U
11

U

U

12

13

Vehicle Class
YEAR

1993
1997
2005

1994
1998
2006

1995
1999
2007

1996
2000
U U U 2008

Figure 18. Typical Arizona Interstate Highway Single Peak VCD.

45

SectionID=4_101849

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure 19. Typical Arizona Non-Interstate Highway Double Peak VCD Found in Urban
Areas or Other Rural Highways.

Table 20. Selection Criteria for Level 3 MEPDG Arizona TTCs Based on Functional Class.
Functional Class
Rural Principal Arterial –
Interstate

Arizona
MEPDG
TTCs
1, 2

Rural Principal Arterial – Other

6, 9, 12

Rural Major Collector
Rural Minor Arterial or
Collector
Urban Principal Arterial –
Interstate

6, 9, 12

Urban Principal Arterial – Other

6, 9, 12, 14
1, 2
9, 12, 14

Arizona Representative Highways
I-8, I-10, I-15, I-19, I-40 (single peak for Class 9)
SR 85, U.S. 60, SR 77, U.S. 93, SR 360, SR 101, SR
303 (double peak for Classes 5 and 9)
U.S. 91 (double peak for Classes 5 and 9)
SR 79, U.S. 60, SR 347
(double peak for Classes 5 and 9)
I-10, I-19, I-40 (some in urban area had double peak
Classes 5 and 9)
SR 360, SR 101, SR 101, SR 303, SR 77
(double peak for Classes 5 and 9)

Analysis of VCD Using Combined ADOT and LTPP Vehicle Classification Data
A cluster analysis similar to that conducted for other inputs was conducted of the combined data
sets of ADOT and LTPP. A summary of all of the sites used in the analysis is shown in Table 21.
The table also shows the final results from the cluster analysis. There were two major groupings
for VCD. A third cluster includes two sections that had a very high percentage of Class 4
vehicles (buses) as the only peak.

46

Table 21. Summary of Cluster Analysis for VCD Using ADOT and LTPP Datasets.
ID

Cluster/Peak

Latitude

Longitude

County

Route

Functional
Class

Route
Type

AADTT

4_0200_R

1P

33.453

-112.74

Maricopa

I-10

RPA-I

I

4820

4_0500_R

1P

32.829

-112.006

Pinal

I-8

RPA-I

I

930

4_0600_R

1P

35.218

-111.564

Coconino

I-40

RPA-I

I

6225

4_100010

1 (2P)

32.7

-114

Yuma

I-08

RPA-I

I

1256

4_100070

1P

33.661

-114.006

La Paz

I-10

RPA-I

I

2978

4_100139

1P

32.454

-111.205

Pima

I-10

UPA-I

I

1980

4_100188

1P

32.341

-109.568

Cochise

I-10

RPA-I

I

2740

4_1001_R

1P

33.461

-112.45

Maricopa

I-10

RPA-I

I

4660

4_1002_R

1P

35.219

-112.49

Yavapai

I-40

RPA-I

I

2310

4_100327

1P

36.98

-113.654

Mohave

I-15

UPA-I

I

1961

4_1003_R

1P

33.481

-112.864

Maricopa

I-10

RPA-I

I

5681

4_100473

1(2P)

32.2

-111

Pima

I-19

UPA-I

I

1311

4_100537

1(2P)

35.23

-111.81

Coconino

I-40

RPA-I

I

2671

4_100541

1(2P)

35.173

-111.647

Coconino

I-40

UPA-I

I

3865

4_1006_R

1P

33.435

-112.661

Maricopa

I-10

RPA-I

I

5740

4_1007_R

1P

33.436

-112.582

Maricopa

I-10

RPA-I

I

5439

4_100922

1P

33.263

-112.634

Maricopa

SR 85

RPA-O

SR

1202

4_1015_R

1P

31.559

-111.052

Santa Cruz

I-19

RPA-I

I

1187

4_1016_R

1P

31.643

-111.058

Santa Cruz

I-19

RPA-I

I

1175

4_1017_R

1P

31.765

-111.036

Pima

I-19

RPA-I

I

1164

4_1018_R

1P

31.807

-111.013

Pima

RPA-I

I

1139

4_102094

1(2P)

34.012

-112.789

Yavapai

I-19
U.S.
93

RPA-O

US

764

4_1022_R

1P

35.161

-113.598

Mohave

I-40

RPA-I

I

2729

4_1024_R

1P

35.278

-113.13

Yavapai

I-40

RPA-I

I

2830

4_1025_R

1P

35.295

-113.029

Yavapai

RPA-I

I

2858

4_1036_R

1P

35.712

-114.481

Mohave

I-40
U.S.
93

RPA-O

US

473

4_1062_R

1P

35.191

-113.347

Mohave

I-40

RPA-I

I

2808

4_1065_R

1P

35.208

-113.268

Yavapai

I-40

RPA-I

I

2802

4_6053_R

1P

31.974

-110.506

Pima

I-10

RPA-I

I

2140

4_6054_R

1P

32.039

-110.993

Santa Cruz

I-19

RPA-I

I

1104

4_6055_R

1P

33.246

-112.638

Maricopa

SR 85

RPA-O

SR

3649

4_6060_R

1P

31.519

-111.017

Santa Cruz

I-19

RPA-I

I

2121

4_7614_R

1P

33.457

-112.325

Maricopa

I-10

RPA-I

I

2667

4_B900_R

1P

33.462

-112.469

Maricopa

I-10

RPA-I

I

5439

4_100767

1P

33.853

-113.907

La Paz

SR 72

RMC

SR

434

4_1021_R

1P

35.161

-113.681

Mohave

I-40

RPA-I

I

2746

Note: Cluster 1 typically has one large peak (1P) for Class 9; Cluster 2 has two peaks, indicated by 2P, for Classes 5
and 9; and Cluster 3 has one peak for Class 4.

47

Table 21. Summary of Cluster Analysis for VCD Using ADOT and LTPP Datasets,
continued.
Functional
Class

Route
Type

AADTT

SR 79

RMA

SR

269

SR 101

UPA-FE

SR

210

SR 303

UPA-FE

SR

826

Pinal

SR 347

RMA

SR

986

-112.415

Maricopa

U.S. 60

RPA-O

US

925

34.209

-110.078

Navajo

U.S. 60

RMA

US

88

2(2P)

35.834

-114.565

Mohave

RPA-O

US

299

4_102230

2(2P)

32.796

-109.54

Graham

U.S. 93
U.S.
191

RMC

US

159

4_7613_R

2(2P)

33.386

-111.839

Maricopa

SR 360

UPA-O

SR

916

4_100800

2(2P)

32.343

-110.977

Pima

SR 77

UPA-O

SR

404

4_7079_R

2(2P)

33.602

-112.253

Maricopa

SR 101

UPA-FE

SR

4498

4_101113

3(Bus)

33.758

-114.217

Yuma

SR 95

RPA-O

SR

201

4_102068

3(Bus)

35.259

-111.551

Coconino

U.S. 89

UPA-O

US

279

ID

Cluster/Peak

Latitude

Longitude

County

4_100854

2(2P)

33.155

-111.356

Pinal

4_101248

2(2P)

33.457

-111.89

Maricopa

4_101602

2(2P)

33.636

-112.418

Maricopa

4_101622

2(2P)

33.092

-112.034

4_101849

2(2P)

33.689

4_101928

2(2P)

4_102084

Route

1P: Denotes one peak for Class 9 vehicles; 2P denotes two peaks for Classes 5 and 9.

Cluster 1 had one large peak for Class 9 vehicles. The percentage ranged from 60 to 80 for this
group. The Class 5 vehicles ranged from 5 to 20 percent. The main functional class highway was
Rural Principal Arterial – Interstate. There were a few sections with two peaks, and these were
usually Urban Principal Arterial – Interstate or Urban Principal Arterial – Other.
Cluster 2 had two large peaks for Class 5 and 9 vehicles. The percentage of Class 5 ranged from
20 to 70 for this group. The percentage of Class 9 ranged from 20 to 40 for this group. The main
functional class highway was Urban Principal Arterial. There were also some Rural Major/Minor
Arterials or Collectors.
Cluster 3 had one large peak for Class 4 vehicles. The percentage of Class 4 vehicles was
approximately 90 percent. These were Rural Principal Arterial and Urban Principal Arterial.
Clusters 1 and 2 can be matched to TTC 2 and TTC 12 very closely, as shown in Table 22.
Note that the results from the two analyses (ADOT sites only, and ADOT and LTPP sites) were
similar, and both were used to develop recommendations for Level 3 MEPDG inputs for VCD
for Arizona’s highway, as discussed in Chapter 6.

48

Table 22. Matching Cluster 1 to TTC 2 and Cluster 2 to TTC 12.
TTC/Cluster

Description

VC4

VC5

VC6

VC7

VC8

VC9

VC10

VC11

VC12

VC13

TTC 2
(1 Peak)

Major
single-trailer
truck route
(Type II)

2.4

14.1

4.5

0.7

7.9

66.3

1.4

2.2

0.3

0.2

Arizona
Cluster 1
(1 Peak)

Primarily
RPA-I

1.8

14.1

2.7

0.1

7.6

66.8

0.7

4.3

1.4

0.5

TTC 12
(2 Peaks)

Intermediate
light and
single-trailer
truck route
(Type III)

3.9

40.8

11.7

1.5

12.2

25.0

2.7

0.6

0.3

1.3

Arizona
Cluster 2
(2 Peaks)

UPA_FE,
RMA, and
RMC (US
and state
routes)

4.7

47.2

7.4

0.4

12.4

25.1

1.7

0.6

0.1

0.4

Several examples of Arizona VCDs that fit into the typical functional classes are provided in
Figures 20 through 29. Appendix B provides plots for VCD for all sites used in this analysis.
SectionID=4_0200_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1994
2007

1995
2008

1996
2009

Figure 20. Plot of VCD for Rural Principal Arterial – Interstate
(Project 4_0200R, I-10, Maricopa County).

49

SectionID=4_1024

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1996

2002

2005

2006

2007

Figure 21. Plot of VCD for Rural Principal Arterial – Interstate
(Project 4_1024, I-40, Yavapai County).
SectionID=4_6055_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20

U

10
0

U
4

5

U

U

U

6

7

8

U
9

10

U
11

U

U

12

13

Vehicle Class
YEAR

1993
1999
2006

1995
2000
U U U 2007

1996
2001
2008

1997
2002

1998
2005

Figure 22. Plot of VCD for Rural Principal Arterial – Other
(Project 4_6055_R, SR 85, Maricopa County).

50

SectionID=4_102094

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure 23. Plot of VCD for Rural Principal Arterial – Other
(Project 4_102094, U.S. 93, Yavapai County).
SectionID=4_101602

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

Vehicle Class
YEAR

2009

Figure 24. Plot of VCD for Urban Principal Arterial
(Project 4_101602, SR 303, Maricopa County).

51

13

SectionID=4_7079_R

Percentage of Trucks

100
90
80
70
60
50
40

U

U

30
20

U

10
0

U
4

U
5

6

7

U
8

9

U

U

10

11

U

U

12

13

Vehicle Class
YEAR

1993
2000
2005

1994
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure 25. Plot of VCD for Urban Principal Arterial
(Project 4_7079_R, SR 101, Maricopa County).
SectionID=4_100854

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

Vehicle Class
YEAR

2009

Figure 26. Plot of VCD for Site Rural Major Arterial
(Project 4_100854, SR 79, Pinal County).

52

13

SectionID=4_101622

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

12

13

Vehicle Class
YEAR

2009

Figure 27. Plot of VCD for Rural Major Arterial
(Project 4_101622, SR 347, Pinal County).
SectionID=4_102230

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

Vehicle Class
YEAR

2009

Figure 28. Plot of VCD for Rural Major Collector
(Project 4_102230, U.S. 191, Graham County).

53

SectionID=4_100767

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure 29. Plot of VCD for Rural Major Collector
(Project 4_100767, SR 72, La Paz County).
HOURLY TRUCK TRAFFIC DISTRIBUTION
Hourly truck distribution data over 24 hours is available for 21 AVC sites and for two LTPP
sections (0100 and 0200). Figure 30 shows the geographical distribution of the AVC sites. A
cluster analysis was performed for the AVC sections. A result of the correlation coefficient
approach to cluster analysis that distinguishes significantly different hourly distributions is
shown in Figure 31, which indicates that there are three distinct clusters. Table 23 summarizes
the actual sections divided into the three clusters. (Note a single section cluster on the far right, a
central cluster, and a cluster located on the right.) The three clusters are described as follows:
1. A cluster that generally represents typical “rural” highway truck distributions. These
sections are labeled Cluster 1 in Table 23 and can be observed in Figure 31 in the center
right (100139, 100327,100767, etc.). The difference between the nighttime and daytime
truck traffic is significant (typically ranges from three to seven), but not as peaked as
typical urban distribution. An example of this “rural” hourly truck distribution is shown
in Figure 32, which is for a site in Coconino County on I-40 (range in hourly percent of
trucks ranges from two at night to seven in the daytime).
2. A cluster that generally represents typical “urban” highway truck distributions. These
sections are labeled Cluster 2 in Table 23 and can be observed in Figure 31 (far left
00473, 00922, 01602, etc.). There is a greater difference between the daytime and
nighttime truck traffic than on rural sites. An example of an “urban” hourly truck
distribution is shown in Figure 33, which is for site 4_100800 located in urban Pima
County on SR 77.

54

Figure 30. Location of AVC Sites in Arizona Used in the Hourly Traffic Analysis.

55

Figure 31. Illustration of a Cluster Analysis for “Correlation Coefficient” to Distinguish
Between Hourly Truck Distributions.

56

Table 23. Summary of Sites and Clusters Determined for
Hourly Truck Traffic Distribution.
SHRP ID

Cluster No.

County

Route ID

Functional Class

Route Type

AADTT

4_100010
4_100139
4_100188
4_100327
4_100537
4_100541
4_100767
4_101113
4_101928
4_102068
4_102094
4_100473
4_100800
4_100854
4_100922
4_101248
4_101602
4_101622
4_101849
4_102084
4_102230
4_100070

1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3

Yuma
Pima
Cochise
Mohave
Coconino
Coconino
La Paz
Yuma
Navajo
Coconino
Yavapai
Pima
Pima
Pinal
Maricopa
Maricopa
Maricopa
Pinal
Maricopa
Mohave
Graham
La Paz

I-08
I-10
I-10
I-15
I-40
I-40
SR 72
SR 95
U.S. 60
U.S. 89
U.S. 93
I-19
SR 77
SR 79
SR 85
SR 101
SR 303
SR 347
U.S. 60
U.S. 93
U.S. 191
I-10

RPA-I
UPA-I
RPA-I
UPA-I
RPA-I
UPA-I
RMC
RPA-O
RMA
UPA-O
RPA-O
UPA-I
UPA-O
RMA
RPA-O
UPA-FE
UPA-FE
RMA
RPA-O
RPA-O
RMC
RPA-I

I
I
I
I
I
I
SR
SR
US
US
US
I
SR
SR
SR
SR
SR
SR
US
US
US
I

1256
1980
2740
1961
2671
3865
434
201
88
279
764
1311
404
269
1202
210
826
986
925
299
159
2978

3. A cluster that represents a long haul section of rural highway across the desert (section
100070 on the western end of I-10 in La Paz County). This section is located in Figure 31
at the far right side. The distribution is shown in Figure 34 and is a very flat truck hourly
distribution with 3 to 4 percent of all trucks being applied at nighttime and increasing to
only 5 percent in the daytime. A similar flat hourly distribution on the same I-10 located
near Phoenix is shown in Figure 35. The U.S. 93 distribution shown in Figure 35 is in a
rural area in the northeastern region of Arizona, which is representative of Cluster 1. The
MEPDG default hourly distribution fits generally between these two distributions.
Plots of all of the hourly data identified for use in this analysis are presented in Appendix C. This
analysis has shown that hourly truck distributions vary across the state and that three Level 2/3
defaults can be provided for three cluster types. Recommendations for the MEPDG Level 2/3
will include three hourly truck distributions representing “rural,” “urban,” and “long-haul desert”
types of highways. The 2/3 level indicates that the hourly truck distributions are correlated to
type of land use for the highway under consideration.

57

SectionID=4_100537

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure 32. Plot of Typical Rural Truck Hourly Distribution for Site 4_100537 Located in
Coconino County on I-40.
The range in hourly distribution of trucks is from 2 percent at nighttime to 7 percent in daytime.
SectionID=4_100800

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure 33. Plot of Typical Urban Truck Hourly Distribution for Site 4_100800 Located in
Urban Pima County (Tucson) on SR 77.
The range in hourly distribution of trucks is from less than 1 percent at nighttime to more than 9
percent in daytime.

58

SectionID=4_100070

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure 34. Plot of Relatively Flat Hourly Distribution for Site 4_100070 from
a Far–Western, Long-Haul Section on I-10 in the Desert.
8
7

Percent Trucks

6
5
4
3
2
1
0
1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
0100

0200

MEPDG

Figure 35. Plot of Three Hourly Truck Distributions.
The hourly truck distributions are (1) site LTPP 0200 west of Phoenix on I-10 showing a
relatively flat long-haul desert distribution, (2) site LTPP 0100 in northwestern Arizona showing
a rural peaked distribution, and (3) the default MEPDG distribution.

59

Monthly Truck Adjustment
The MAF input in the MEPDG provides the opportunity to fine-tune the design considering
month-to-month truck volumes. The national defaults were 1.00 for each month, which provides
for the same truck volume each month of a given year.
The MAF was computed for a number of sites in Arizona to determine variations around the
state. A cluster analysis was conducted using the data from 22 AVC sites in Arizona, as shown
on the map in Figure 36. Details of the 22 sites are provided in Table 24.
A cluster analysis similar to that conducted for other MEPDG traffic inputs was conducted.
Results from the correlation coefficient approach are shown in Figure 37. These analyses were
conducted using Class 5 and Class 9 vehicles.
The overall results from this and the other methods show that the MAF factors break down into a
single cluster with two outliers. It is certainly possible to have “outliers” that represent a
significantly different MAF; however, by far the most Arizona sections had MAF that do not
vary significantly from each other in terms of Class 5 and Class 9 trucks. The analysis included
only sections with all 12 months of MAF.

60

Figure 36. Locations of AVC Sites Used in the Analysis of
Monthly Truck Adjustment Factors.
61

Table 24. AVC Sites Used in the Monthly Truck Adjustment Factors.
SHRP ID

Cluster
No.

Vehicle
Class

Latitude,
deg.

Longitude,
deg.

County

Route
ID

Functional
Class

Route
Type

AADTT

4_100010

1

MAF5

32.7

-114

Yuma

I-08

RPA-I

I

1256

4_100010

1

MAF9

32.7

-114

Yuma

I-08

RPA-I

I

1256

4_100139

1

MAF9

32.454

-111.205

Pima

I-10

UPA-I

I

1980

4_100188

1

MAF5

32.341

-109.568

Cochise

I-10

RPA-I

I

2740

4_100188

1

MAF9

32.341

-109.568

Cochise

I-10

RPA-I

I

2740

4_100473

1

MAF5

32.2

-111

Pima

I-19

UPA-I

I

1311

4_100473

1

MAF9

32.2

-111

Pima

I-19

UPA-I

I

1311

4_100537

1

MAF9

35.23

-111.81

Coconino

I-40

RPA-I

I

2671

4_100541

1

MAF5

35.173

-111.647

Coconino

I-40

UPA-I

I

3865

4_100541

1

MAF9

35.173

-111.647

Coconino

I-40

UPA-I

I

3865

4_100767

1

MAF5

33.853

-113.907

La Paz

SR 72

RMC

SR

434

4_100767

1

MAF9

33.853

-113.907

La Paz

SR 72

RMC

SR

434

4_100854

1

MAF5

33.155

-111.356

Pinal

SR 79

RMA

SR

269

4_100854

1

MAF9

33.155

-111.356

Pinal

SR 79

RMA

SR

269

4_100922

1

MAF5

33.263

-112.634

Maricopa

SR 85

RPA-O

SR

1202

4_100922

1

MAF9

33.263

-112.634

Maricopa

SR 85

RPA-O

SR

1202

4_101622

1

MAF5

33.092

-112.034

Pinal

SR 347

RMA

SR

986

4_101622

1

MAF9

33.092

-112.034

Pinal

SR 347

RMA

SR

986

4_101849

1

MAF5

33.689

-112.415

Maricopa

U.S. 60

RPA-O

US

925

4_101849

1

MAF9

33.689

-112.415

Maricopa

U.S. 60

RPA-O

US

925

4_101928

1

MAF5

34.209

-110.078

Navajo

U.S. 60

RMA

US

88

4_101928

1

MAF9

34.209

-110.078

Navajo

U.S. 60

RMA

US

88

4_102084

1

MAF5

35.834

-114.565

Mohave

U.S. 93

RPA-O

US

299

4_102084

1

MAF9

35.834

-114.565

Mohave

U.S. 93

RPA-O

US

299

4_100139

2

MAF5

32.454

-111.205

Pima

I-10

UPA-I

I

1980

4_100537

3

MAF5

35.23

-111.81

Coconino

I-40

RPA-I

I

2671

62

Figure 37. Results from the Correlation Coefficient Method for
Monthly Truck Adjustment Factors.
Plots of MAF for several of the AVC sites are shown in Figure 38 through Figure 41. MAF plots
for all of the projects used in this analysis are presented in Appendix D.
Statistically, all of these MAF factors are the same. The main question is whether these monthly
variations will cause a significant change in the pavement design. While some of these plots
show differences from month to month that may appear to be significant, some designs prepared
with the MEPDG with these monthly distribution factors showed no significant thickness
differences for HMA (fatigue damage) or PCC thickness (fatigue damage) to control structural
damage.
Thus, it is concluded that while Level 1 MAFs can be obtained with on-site AVCs, using straight
1.00 for every month for Level 3 would not normally produce a different required thickness.

63

SectionID=4_100188

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

NOV

DEC

West

Month
Figure 38. Plot of MAF for Site 4_100188
(Vehicle Class 5), I-10 in Cochise County.
SectionID=4_100188

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

West

Month
Figure 39. Plot of MAF for Site 4_100188
(Vehicle Class 9), I-10 in Cochise County.

64

SectionID=4_100541

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

NOV

DEC

West

Month
Figure 40. Plot of MAF for Site 4_100541
(Vehicle Class 5), I-40 in Coconino County.
SectionID=4_100541

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

West

Month
Figure 41. Plot of MAF for Site 4_100541
(Vehicle Class 9), I-40 in Coconino County.

65

AXLE LOAD DISTRIBUTION
The ALD for a given highway section affects the load applied to the pavement by each single,
tandem, tridem, and quad axles that pass over the given section during the design period, and it is
an important MEPDG input. ALD data were analyzed using data representing 29 ADOT LTPP
project sites. A map showing the locations of the project sites is shown in Figure 42.

Figure 42. Locations of the LTPP Sites with WIM Data.

66

Data were evaluated from the 29 sites to help derive Level 3 defaults for MEPDG traffic inputs.
The MEPDG includes national recommendations or default ALD (based on averages from over
100 sites located across the United States) for all four axle types. Of primary interest is how well
the national defaults match local Arizona ALD, and if there is the need for Arizona-specific ALD
defaults. Based on this information, Arizona-specific ALDs can be derived as needed.
The predominant truck types on Arizona highways are Classes 5 and 9. Emphasis was placed on
how ALD for Classes 5 and 9 match with national defaults. Note that the predominant axle type
for Class 5 trucks is single, and Class 9 trucks include both single and tandem.
For comparative purposes, the default MEPDG ALD and ALD from selected ADOT LTPP sites
are shown in Figure 43 through Figure 45. Also included in these plots are the MEPDG default
ALD.
40

Percentage of all axles

35
30

25
20
15
10
5
0
0

5000

10000

15000

20000

25000

30000

35000

40000

45000

Axle load, Ibs
4_0100

4_0200

4_0500

4_0600

4_0900

4_1001

4_1002

4_1006

4_1007

4_1016

4_1017

4_1018

4_1021

4_1022

4_1024

4_1025

4_1034

4_1036

4_1062

4_1065

4_6053

4_6054

4_6055

4_6060

4_7079

4_7613

4_7614

4_A900

4_B900

MEPDG

Figure 43. Typical Arizona Highway Class 5 Truck Single-Axle Load Distribution.

67

Percentage of all axles

35
30
25
20

15
10
5
0

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

Axle load, Ibs
4_0100

4_0200

4_0500

4_0600

4_0900

4_1001

4_1002

4_1006

4_1007

4_1016

4_1017

4_1018

4_1021

4_1022

4_1024

4_1025

4_1034

4_1036

4_1062

4_1065

4_6053

4_6054

4_6055

4_6060

4_7079

4_7613

4_7614

4_A900

4_B900

MEPDG

Figure 44. Typical Arizona Highway Class 9 Truck Single-Axle Load Distribution.

20
18

Percentage of all axles

16
14
12
10
8
6
4
2
0
0

10000

20000

30000

40000

50000

60000

70000

80000

90000

Axle load, Ibs
4_0100

4_0200

4_0500

4_0600

4_0900

4_1001

4_1002

4_1006

4_1007

4_1016

4_1017

4_1018

4_1021

4_1022

4_1024

4_1025

4_1034

4_1036

4_1062

4_1065

4_6053

4_6054

4_6055

4_6060

4_7079

4_7613

4_7614

4_A900

4_B900

MEPDG

Figure 45. Typical Arizona Highway Class 9 Truck Tandem-Axle Load Distribution.

68

A review of the ALD plots showed the following:
Class 5 and Class 9 single ALD exhibited a single peak load. The peak load ranged from
5,000 to 7,000 lb for Class 5 single axles and 11,000 to 15,000 lb for Class 9 single axles.
This distribution is typical of Arizona highways in rural and urban areas; however, a few
of these Class 9 trucks showed single axles with significantly higher axle loads when
compared to other sites within the state.
For both Class 5 and Class 9 single ALD, the Arizona sites exhibited higher peak loads
when compared to the MEPDG national defaults.
Class 9 tandem ALD exhibited two peak loads. The peak loads ranged from 12,000 to
18,000 lb and 32,000 to 38,000 lb.
ALD data from the 29 LTPP sites were analyzed to develop clusters for Level 3 Arizona ALD
defaults. The results are presented in the following sections.
Cluster Analysis of ADOT LTPP ALD Data
A cluster analysis similar to that conducted for other inputs was conducted using all LTPP sites
with WIM and ALD data. The data were reviewed and cleaned as previously described prior to
performing this cluster analysis. ALD data from specific years that were deemed outliers or
obvious data errors were excluded from this analysis. The reasons for deviations from the typical
distributions included local construction resulting in roadway closures, construction of new
routes leading to the permanent diversion of traffic, and problems with WIM equipment. Specific
data not included in this analysis are shown in Table 25.

69

Table 25. Summary of Outlier Data Excluded from the Cluster Analysis.
Section ID

Year

4_0100

2004

4_0600

2002

4_0600

2003

4_0900

2004

4_6060

1998

4_A900

2004

4_B900

1997

4_B900

1998

4_0100

2006

4_0500

2008

4_0600

2002

4_0600

2003

4_1002

1999

4_1002

2005

4_1007

2000

4_1007

2001

4_1007

2002

4_1007

2003

4_6055

2001

4_6055

2002

4_7079

1993

4_7079

1994

4_B900

2000

4_B900

2001

4_B900

2002

4_B900

2003

4_0100

2006

4_0600

2002

4_0600

2003

4_1002

1999

4_1007

2000

4_6055

2001

4_6055

2002

4_7079

1993

4_7079

1994

4_7614

1993

Vehicle Class and Axle Type

Class 5, Single Axles

Class 9, Single Axles

Class 9, Tandem Axles

70

Figure 46 through Figure 48 show ALD for Class 5 and Class 9 trucks, and Table 26 shows the
final results from the ALD cluster analysis. The cluster analysis showed that there were three
major groupings for ALD and a possible sub-grouping within Cluster 1. All of the three main
Arizona groupings were different from the MEPDG default ALD for Class 5 and Class 9 single
axles and Class 9 tandem axles.
Cluster 1: This distribution had one large peak for Class 5 single axles. The peak corresponded
with approximately 6,000 lbs of weight. The percentage of single axles at this weight was
approximately 25. The Class 9 single axles that also had a large peak corresponded with
approximately 11,000 lbs of weight. The percentage of single axles at this weight was
approximately 20. For Class 9 tandems, the ALD had two large peaks. The difference in
percentage of axles at the peaks was quite small (i.e., 2 percent). The heavier peak exhibited a
higher percentage of axles. The main functional class highway was Rural Principal Arterial –
Interstate.
Cluster 2: This distribution had one large peak for Class 5 single axles. The peak corresponded
with approximately 6,000 lbs of weight. The percentage of single axles at this weight was
approximately 25. The Class 9 single axles that also had a large peak corresponded with
approximately 11,000 lbs of weight. The percentage of single axles at this weight was
approximately 16. For Class 9 tandems, ALD had two large peaks. The difference in percentage
of axles at the peaks was quite small (i.e., 2.5 percent). The heavier peak exhibited a lower
percentage of axles. The main functional class highway was urban freeways and rural minor
arterials/collectors.
Cluster 3: This distribution had one large peak for Class 5 single axles. The peak corresponded
with approximately 6,000 lbs of weight. The percentage of single axles at this weight was
approximately 32.5. This was significantly higher than those reported for Clusters 1 and 2. The
Class 9 single axles that also had a large peak corresponded with approximately 11,000 lbs of
weight. The percentage of single axles at this weight was approximately 25 (higher than that
reported for Clusters 1 and 2). For Class 9 tandems, ALD had two large peaks. The difference in
percentage of axles at the peaks was significant (i.e., 10 percent). The heavier peak exhibited a
significantly higher percentage of axles. The main functional class highway was rural principal
arterial (non-Interstates).
None of the Arizona-derived clusters matched with the MEPDG defaults. Plots of ALD for all of
the projects analyzed are presented in Appendix E.

71

Figure 46. Single-Axle Load Distribution for Truck Class 5.

Figure 47. Single-Axle Load Distribution for Truck Class 9.

72

Figure 48. Tandem-Axle Load Distribution for Truck Class 9.

73

Table 26. Summary of Cluster Analysis for ALD Using ADOT and LTPP Datasets.
ID

S5,
Cluster

ID

S9,
Cluster

ID

T9,
Cluster

County

Route

FClass

Route Type

AADTT

4_0500

1

4_0500

1

4_0500

1

Pinal

I-08

RPA-I

I

930

4_1001

1

4_1001

1

4_1001

1

Maricopa

I-10

RPA-I

I

4660

4_1006

1

4_1006

1

4_1006

1

Maricopa

I-10

RPA-I

I

5740

4_1007

1

4_1007

1

4_1007

1

Maricopa

I-10

RPA-I

I

5439

4_6053

1

4_6053

1

4_6053

1

Pima

I-10

RPA-I

I

2140

74

4_B900

1

4_B900

1

4_B900

1

Maricopa

I-10

RPA-I

I

5439

4_0200**

2

4_0200

1

4_0200

1

Maricopa

I-10

RPA-I

I

4820

4_7614**

2

4_7614

1

4_7614

1

Maricopa

I-10

RPA-I

I

2667

4_1016

1

4_1016

1

4_1016

1

Santa Cruz

I-19

RPA-I

I

1175

4_6054**

2

4_6054

1

4_6054

1

Santa Cruz

I-19

RPA-I

I

1104

4_1018**

2

4_1018*

2

4_1018*

2

Pima

I-19

RPA-I

I

1139

4_6060**

3

4_6060

1

4_6060

1

Santa Cruz

I-19

RPA-I

I

2121

4_1017**

5

4_1017*

4

4_1017

1

Pima

I-19

RPA-I

I

1164

4_1021

1

4_1021

1

4_1021

1

Mohave

I-40

RPA-I

I

2746

4_1022

1

4_1022

1

4_1022

1

Mohave

I-40

RPA-I

I

2729

4_1024

1

4_1024

1

4_1024

1

Yavapai

I-40

RPA-I

I

2830

4_1062

1

4_1062

1

4_1062

1

Mohave

I-40

RPA-I

I

2808

4_1065

1

4_1065

1

4_1065

1

Yavapai

I-40

RPA-I

I

2802

4_1025

1

4_1025*

2

4_1025*

3

Yavapai

I-40

RPA-I

I

2858

4_0600**

2

4_0600

1

4_0600

1

Coconino

I-40

RPA-I

I

6225

4_1002**

3

4_1002*

5

4_1002*

6

Yavapai

I-40

RPA-I

I

2310

4_7079

1

4_7079

1

4_7079

1

Maricopa

SR 101

UPA-FE

SR

4498

4_7613

1

4_7613

1

4_7613

2

Maricopa

SR 360

UPA-O

SR

916

4_6055

3

4_6055

1

4_6055

5

Maricopa

SR 85

RPA-O

SR

3649

4_1034

2

4_1034

1

4_1034

2

LaPaz

SR 95

RMA

SR

1111

4_0100

2

4_0100

1

4_0100

1

Mohave

U.S. 93

RPA-O

US

410

4_0900

2

4_0900

1

4_0900

1

Mohave

U.S. 93

RPA-O

US

420

4_1036

2

4_1036

1

4_1036

1

Mohave

U.S. 93

RPA-O

US

473

4_A900

2

4_A900

1

4_A900

1

Mohave

U.S. 93

RPA-O

US

420

MEPDG

4

MEPDG

3

MEPDG

4

Cluster Combined

Rural principal arterial
(Interstates)

Urban freeways and
rural minor
arterials/collectors

Rural principal arterial
(non-Interstates)

National default

Cluster 1 typically has one large peak (1P) for Class 9; Cluster 2 has two peaks, indicated by 2P, for Classes 5 and 9; and Cluster 3 has one peak for Class 4.

AXLES PER TRUCK
The numbers of single, tandem, tridem, and quad axles per truck are used to determine the total
number of axles of each type to pass over the design traffic lane over the analysis period. For
some trucks, such as Class 5, the number of single axles is set by the classification criteria at
2.00. For others, this value varies somewhat depending on the definition of the classification.
A cluster analysis was conducted using 33 LTPP sites in Arizona for Class 9 trucks to determine
if there were any significant differences in axles per truck across the state. As a result, none are
expected since a Class 9 truck is specified to have one single and two tandem axles. The sites are
shown in Figure 49.

Figure 49. Map of Sites Used for the Axles-Per-Truck Analysis.
75

A summary of the cluster analysis is provided in Table 27. The cluster analysis indicates that a
single cluster for Class 9 trucks and some outliers explain the data. This result indicates that the
various sites shown in Figure 49 do not show significantly different axles per truck values.
Several plots of the Class 9 tandem cluster of axles are provided as Figures 50 through 53. Plots
of axles per truck for all of the projects analyzed are presented in Appendix F.
Table 27. Summary of All Sites Used in the Axles-per-Truck Cluster Analysis.
ID

Tandem
Axle
Cluster

Latitude,
deg.

Longitud
e, deg.

County

Route

Functiona
l Class

Route
Type

AADTT

4_1003

1

33.48

-112.86

Maricopa

I-10

RPA-I

I

5681

4_1015

1

31.56

-111.05

Santa Cruz

I-19

RPA-I

I

1187

4_1037

1

35.19

-114.55

Mohave

SR 68

RPA-O

SR

2057

4_1065

2

35.21

-113.27

Yavapai

I-40

RPA-I

I

2802

4_6054

2

32.04

-110.99

Santa Cruz

I-19

RPA-I

I

1104

4_0100

2

35.40

-114.26

U.S. 93

RPA-O

US

410

4_0200

2

33.45

-112.74

Maricopa

I-10

RPA-I

I

4820

4_0500

2

32.83

-112.01

Pinal

I-08

RPA-I

I

930

4_0600

2

35.22

-111.56

Coconino

I-40

RPA-I

I

6225

4_0900

2

35.39

-114.26

U.S. 93

RPA-O

US

420

4_1001

2

33.46

-112.45

Maricopa

I-10

RPA-I

I

4660

4_1002

2

35.22

-112.49

Yavapai

I-40

RPA-I

I

2310

4_1006

2

33.44

-112.66

Maricopa

I-10

RPA-I

I

5740

4_1007

2

33.44

-112.58

Maricopa

I-10

RPA-I

I

5439

4_1016

2

31.64

-111.06

Santa Cruz

I-19

RPA-I

I

1175

4_1018

2

31.81

-111.01

Pima

I-19

RPA-I

I

1139

4_1021

2

35.16

-113.68

Mohave

I-40

RPA-I

I

2746

4_1022

2

35.16

-113.60

Mohave

I-40

RPA-I

I

2729

4_1024

2

35.28

-113.13

Yavapai

I-40

RPA-I

I

2830

4_1025

2

35.30

-113.03

Yavapai

I-40

RPA-I

I

2858

4_1034

2

34.16

-114.27

La Paz

SR 95

RMA

SR

1111

4_1036

2

35.71

-114.48

Mohave

U.S. 93

RPA-O

US

473

4_1062

2

35.19

-113.35

Mohave

I-40

RPA-I

I

2808

4_6053

2

31.97

-110.51

Pima

I-10

RPA-I

I

2140

4_6055

2

33.25

-112.64

Maricopa

SR 85

RPA-O

SR

3649

4_6060

2

31.52

-111.02

Santa Cruz

I-19

RPA-I

I

2121

4_7079

2

33.60

-112.25

Maricopa

SR 101

UPA-FE

SR

4498

4_7613

2

33.39

-111.84

Maricopa

SR 360

UPA-O

SR

916

4_7614

2

33.46

-112.33

Maricopa

I-10

RPA-I

I

2667

4_A900

2

35.39

-114.26

U.S. 93

RPA-O

US

420

4_B900

2

33.46

-112.47

Maricopa

I-10

RPA-I

I

5439

4_1017

3

31.77

-111.04

Pima

I-19

RPA-I

I

1164

76

SectionID=0500

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure 50. Plot of Axles per Truck for Site 4_0500 (Vehicle Class 9).
SectionID=1002
5

Axles per Truck

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure 51. Plot of Axles per Truck for Site 4_1002 (Vehicle Class 9).

77

SectionID=1007

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure 52. Plot of Axles per Truck for Site 4_1007 (Vehicle Class 9).
SectionID=6055

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure 53. Plot of Axles per Truck for Site 4_6055 (Vehicle Class 9).

78

CHAPTER 5. SENSITIVITY ANALYSIS
A sensitivity analysis was conducted to determine the impact of the identified clusters on
pavement design and to revise the clusters as needed. Typical ADOT designs for new HMA
pavement and new JPCP were used as baseline pavement designs for the sensitivity analysis.
This chapter presents a description of the baseline pavement designs along with traffic inputs
(MEPDG inputs representing the various clusters identified) and sensitivity analysis results.
DESCRIPTION OF BASELINE PAVEMENT DESIGNS
Baseline New HMA Pavement Design
The baseline HMA pavement was modeled after LTPP project 1003 in Arizona (located on I-10,
Rural Principal Arterial, in Maricopa County). The project consisted of 6-inch HMA over a 6inch AASHTO soil class A-1, and a granular base constructed over a granular subgrade
(AASHTO soil class A-2-6). MEPDG default inputs for all of the materials were assumed (see
Table 28). Traffic volume is shown in Figure 54. National defaults were assumed for all other
MEPDG traffic inputs. Climate data were obtained from the four closest weather stations to the
project in the Phoenix/Scottsdale area (see Figure 55). An analysis period of 20 years was
assumed. Only the HMA pavement distress type influenced by traffic (namely alligator cracking,
rutting, and International Roughness Index [IRI]) were considered in the sensitivity analysis.
Table 28. HMA Pavement Materials Properties.
Layer Type

HMA

Granular Base

Subgrade

Properties
Thickness: 6 inches
Gradation:
Sieve Size
Percent Retained or Passing
¾-inch
7
⅜-inch
32.5
No. 4
48
No. 200 (passing)
4.1
Volumetric Properties:
Effective binder content
11.6 percent by volume
Air voids
7 percent
Bulk unit weight
150 pcf
AASHTO soil class
A-1-a
Resilient modulus (at optimum)
29,500 psi
Maximum dry density
127.7 pcf
Optimum moisture content
7.4 percent
AASHTO soil class
A-2-6
Resilient modulus (at optimum)
20,500 psi
Max. dry density
121.9 pcf
Optimum moisture content
10.0 percent

79

Figure 54. Baseline Traffic Volume Inputs Used for Sensitivity Analysis.

Figure 55. Location of Climate Stations for Baseline HMA Pavement Project.

80

Baseline New JPCP Design
The baseline JPCP was modeled after LTPP project 7613 in Arizona (located on SR 360/60,
Urban Principal Arterial, in Maricopa County). The project consisted of 9-inch PCC over a 12inch AASHTO soil class 2-2-7 granular base constructed over a granular subgrade (AASHTO
soil class A-2-7). MEPDG default inputs for all of the materials were assumed (see Table 29).
The traffic volume was as shown in Figure 54 (for new HMA pavement). National defaults were
assumed for all other MEPDG traffic inputs for the baseline project. Climate data were obtained
from the three closest weather stations to the project in the Phoenix/Scottsdale area (see Figure
56). An analysis period of 30 years was assumed. Only the JPCP distress types influenced by
traffic (transverse cracking, faulting, and IRI) were considered in the sensitivity analysis.
Table 29. JPCP Materials Properties.
Layer Type

PCC

Granular Base

Subgrade

Properties
Thickness: 9 inches
Strength
28-day flexural strength
684 psi
28-day elastic modulus
3,770,000
Coef. of thermal expansion
5.5/deg. C
AASHTO soil class
A-2-7
Resilient modulus (at optimum)
16,000 psi
Maximum dry density
121.0 pcf
Optimum moisture content
10.8 percent
AASHTO soil class
A-2-6
Resilient modulus (at optimum)
16,000 psi
Maximum dry density
120.4 pcf
Optimum moisture content
10.8 percent

Figure 56. Location of Climate Stations for Baseline HMA Pavement Project.

81

MEPDG TRAFFIC INPUTS USED FOR SENSITIVITY ANALYSIS
All of the natural clusters identified in Chapter 4 were considered for use in this sensitivity
analysis. The representative MEPDG input for a given cluster (e.g., ALD) was the average of all
ALD for projects that fall within the given cluster. Based on the outcome of this cluster analysis,
the clusters presented in Table 30 were used for this sensitivity analysis. Figures 57 through 61
show plots of the clusters used for sensitivity analysis for VCD, ALD, and hourly distribution.
Table 30. MEPDG Traffic Input Data Clusters Used for Sensitivity Analysis.
MEPDG Data Type
Vehicle class distribution

Number of Clusters
2

Axle load distribution

3

Hourly distribution

3*

Monthly adjustment factors

1

Axles per truck
1**
*The third cluster consisted of a single project. This cluster was not considered.
**Identified outliers were not considered.

100
90
80

Percent Trucks

70
60
50
40
30
20

10
0
4

5

6

7

8

9

10

11

12

Vehicle Class
Cluster 1

Cluster 2

Figure 57. Plot of VCD for Clusters 1 and 2 and the MEPDG Default.

82

13

Truck Class 5, Single ALD
Percentage of all axles

35

30
25
20
15

10
5
0
0

10000

20000

30000

40000

50000

Axle load, lbs
Cluster 1

Cluster 2

Cluster 3

MEPDG

Figure 58. Plot of Single ALD for Clusters 1, 2, and 3 (Class 5 Trucks Only).

Truck Class 9, Single ALD
30

Percentage of all axles

25
20
15

10
5
0
0

10000

20000

30000

40000

50000

Axle load, lbs
Cluster 1

Cluster 2

Cluster 3

MEPDG

Figure 59. Plot of Single ALD for Clusters 1 and 2 (Class 9 Trucks Only).

83

Truck Class 9, Tandem ALD
18

Percentage of all axles

16

14
12
10
8
6
4

2
0
0

20000

40000

60000

80000

100000

Axle load, lbs
Cluster 1

Cluster 2

Cluster 3

MEPDG

Figure 60. Plot of Tandem ALD for Clusters 1 and 2 (Class 9 Trucks Only).
8
7

Percentage of all trucks

6
5
4
3
2
1
0

0

2

4

6

8

10

12

14

16

18

20

22

24

Hour
Cluster 1

Cluster 2

MEPDG

Figure 61. Plot of Hourly Distribution for Clusters 1 and 2 and the MEPDG Default.

84

SENSITIVITY ANALYSIS RESULTS
Vehicle Class Distribution
Sensitivity analysis results showing the impact of VCD from the two Arizona clusters are
presented in Figures 62 through 67. A sensitivity analysis was performed using typical Arizona
HMA and JPCP projects (LTPP projects 1003 and 7613 for HMA and JPCP, respectively, with
some modifications to JPCP design features and base year AADTT).
HMA thickness was varied from 4 to 14 inches until an adequate design was achieved. All
distresses were below terminal values: alligator cracking = 20 percent lane area, total rutting =
0.75 inches. It is worth noting that it is obvious from these analyses that rutting is over-predicting
and will need local calibration, and IRI = 172 inches/mile at 90 percent reliability .
PCC thickness was varied from 8 to 12 inches until an adequate design was achieved. All
distresses were below terminal values: faulting = 0.12 inches, cracking = 15 percent, and IRI =
172 inches/mile at 90 percent reliability. The sensitivity analysis results are summarized in Table
31.
The sensitivity analysis results show a significant impact of VCD (Arizona Clusters 1 and 2) on
both HMA and JPCP design. For HMA pavements, the difference in HMA thickness (depending
on the selected failure criterion) ranged from 4.3 to 28.6 percent. For JPCP, the difference in
PCC thickness (depending on the selected failure criterion) ranged from 2.9 to 9.4 percent. The
difference in overall design thickness was 4.3 percent for new HMA pavements and 5.7 percent
for new JPCP. The impact of this on pavement construction costs will be significant.
100
90

Reliability, percent

80
70
60
50

40
30
20
10
0
4

6

8

10

12

HMA thickness, in
Cluster 1

Cluster 2

Figure 62. Plot Showing the Effect of VCD Clusters 1 and 2 on
New HMA Pavement Alligator Cracking.

85

14

100
90

Reliability, percent

80
70
60
50

40
30

20
10

0
4

6

8

10

12

14

HMA thickness, in
Cluster 1

Cluster 2

Figure 63. Plot Showing the Effect of VCD Clusters 1 and 2 on
New HMA Pavement Rutting.
100

90
Reliability, percent

80
70
60
50
40
30
20
10

0
4

6

8

10

12

14

HMA thickness, in
Cluster 1

Cluster 2

Figure 64. Plot Showing the Effect of VCD Clusters 1 and 2 on New HMA Pavement IRI.

86

100
90

Reliability, percent

80

70
60
50
40
30
20

10.2-in

10
0
8

9

10

11

12

PCC thickness, in
Cluster 1

Cluster 2

Figure 65. Plot Showing the Effect of VCD Clusters 1 and 2
on New JPCP Transverse Cracking.
100
90

Reliability, percent

80
70

60
50
40
30
20
10
0
8

9

10

11

12

13

PCC thickness, in
Cluster 1

Cluster 2

Figure 66. Plot Showing the Effect of VCD Clusters 1 and 2 on New JPCP Faulting.

87

100
90

Reliability, percent

80

70
60
50
40
30
20
10
0
8

9

10

11

12

13

PCC thickness, in
Cluster 1

Cluster 2

Figure 67. Plot Showing the Effect of VCD Clusters 1 and 2 on New JPCP IRI.
Table 31. Summary of Sensitivity Results for VCD.
Pavement
Type

Distress/IRI

Alligator cracking
Rutting
IRI
HMA overall design
Transverse cracking
JPCP
Faulting
IRI
JPCP overall design
HMA

Design HMA/PCC Thickness at 90
Percent Reliability, in.
Cluster 1
Cluster 2
6.9
6.1
13.9
13.3
9.1
6.5
13.9
13.3
10.2
9.9
12.2
11.5
11.7
10.6
12.2
11.5

Percent
Difference
11.6
4.3
28.6
4.3
2.9
5.7
9.4
5.7

Axle Load Distribution
Sensitivity analysis results showing the impact of ALD from the three Arizona clusters and
MEPDG national defaults are presented in Figures 68 through 73. Sensitivity analysis was
performed using the typical Arizona LTPP projects as described for VCD. The sensitivity
analysis results are summarized in Table 32.
The sensitivity analysis showed mixed results. Depending on the distress type of interest in
setting the design criteria, the ALD could have a significant impact on thickness (6.7 percent
difference in HMA thickness for alligator cracking, 7.1 percent difference in HMA thickness for
HMA IRI, and a 3.9 percent difference in PCC thickness for transverse cracking).
However, the analysis results showed no significant impact of ALD (Arizona clusters and
MEPDG national default) on overall HMA and JPCP design. This was because, for new HMA
88

pavement, overall HMA thickness was based on rutting, which showed no significant
difference for ALD. For both HMA rutting and JPCP faulting and IRI, it may be that the very
high axle loads that cause most of the permanent strains in HMA, fatigue damage, and faulting
erosion in PCC are not very different for the three clusters.
100
90
Reliability, percent

80
70
60
50

40
30
20
10
0
4

6

8

10

12

14

HMA thickness, in
Cluster 1

Cluster 2

Cluster 3

Default ALD

Figure 68. Plot Showing the Effect of ALD Clusters 1 through 3
on New HMA Pavement Alligator Cracking.
100
90

Reliability, percent

80
70

60
50

40
30

20
10

0
4

6

8

10

12

HMA thickness, in
Cluster 1

Cluster 2

Cluster 3

Default ALD

Figure 69. Plot Showing the Effect of ALD Clusters 1 through 3
on New HMA Pavement Rutting.

89

14

100
90

Reliability, percent

80
70
60
50
40
30

20
10

0
4

6

8

10

12

14

HMA thickness, in
Cluster 1

Cluster 2

Cluster 3

Default ALD

Figure 70. Plot Showing the Effect of ALD Clusters 1 through 3
on New HMA Pavement IRI.
100
90

Reliability, percent

80

70
60
50
40
30
20
10
0
8

9

10

11

PCC thickness, in
Cluster 1

Cluster 2

Cluster 3

MEPDG

Figure 71. Plot Showing the Effect of ALD Clusters 1 through 3
on New JPCP Transverse Cracking.

90

12

100
90

Reliability, percent

80
70

60
50
40
30
20
10
0
8

9

10

11

12

PCC thickness, in
Cluster 1

Cluster 2

Cluster 3

MEPDG

Figure 72. Plot Showing the Effect of ALD Clusters 1 through 3 on New JPCP Faulting.
100
90

Reliability, percent

80

70
60
50
40
30
20
10
0
8

9

10

11

12

PCC thickness, in
Cluster 1

Cluster 2

Cluster 3

MEPDG

Figure 73. Plot Showing the Effect of ALD Clusters 1 through 3 on New JPCP IRI.

91

Table 32. Summary of Sensitivity Results for ALD.
Pavement
Type

Distress/IRI

Design HMA/PCC Thickness at 90 Percent
Reliability, in.
Cluster 1 Cluster 2 Cluster 3
MEPDG

Percent
Difference*

Alligator
7.3
7.0
7.5
6.8
6.7
cracking
HMA
Rutting
14.1
14
14.1
13.9
0.7
IRI
9.5
9.1
9.8
8.7
7.1
HMA overall design
14.1
14
14.1
13.9
0.7
Transverse
9.9
9.9
10.3
9.9
3.9
cracking
JPCP
Faulting
11.9
11.9
11.8
11.5
0.8
IRI
10.9
10.9
10.8
10.6
0.9
JPCP overall Design
11.9
11.9
11.8
11.5
0.8
*Computed using the maximum and minimum thickness required for the three Arizona clusters.

Hourly Distribution
Sensitivity analysis results showing the impact of hourly truck distribution are presented in
Figures 74 through 76. Sensitivity analysis results are presented only for JPCP, as the hourly
truck distribution has no impact on HMA pavements. The sensitivity analysis results show that
the Arizona hourly truck distribution clusters had no significant impact on PCC thickness and the
overall design.
100
90

Reliability, percent

80

70
60
50
40
30
20
10
0
8

9

10

11

12

PCC thickness, in
Cluster 1

Cluster 2

Cluster 3

MEPDG2

Figure 74. Plot Showing the Effect of Hourly Distribution Clusters 1 and 2 on
New JPCP Transverse Cracking.

92

100
90

Reliability, percent

80
70

60
50
40
30
20
10
0
8

9

10

11

12

PCC thickness, in
Cluster 1

Cluster 2

Cluster 3

MEPDG

Figure 75. Plot Showing the Effect of Hourly Distribution Clusters 1 and 2on
New JPCP Faulting.
100
90

Reliability, percent

80

70
60
50
40
30
20
10
0
8

9

10

11

PCC thickness, in
Cluster 1

Cluster 2

Cluster 3

MEPDG

Figure 76. Plot Showing the Effect of Hourly Distribution
Clusters 1 and 2 on New JPCP IRI.

93

12

94

CHAPTER 6. DEVELOPMENT OF STATEWIDE LEVEL 2/3 MEPDG
TRAFFIC INPUTS
The results of the statistical cluster analysis and sensitivity analysis were used to develop typical
MEPDG Level 2/3 traffic inputs. This chapter presents the defaults developed for the following:
VCD.
Hourly distribution.
MAF.
ALD.
Number of axles per truck.
Lateral wander.
Truck wheelbase.
VEHICLE CLASS DISTRIBUTION
The statistical analysis identified two VCD clusters in Arizona. The sensitivity analysis confirms
that the three identified clusters produced significantly different new HMA and new JPCP
designs. Thus, the application of two VCD clusters for MEPDG pavement design is
recommended. A description of the two VCD clusters is presented in Table 33.
Table 33. Recommended MEPDG VCD Inputs for Level 2/3 Design in Arizona.
Vehicle
Class

Cluster 1—Major Single Truck
Trailer Route, Primarily Rural
Principal Arterial

Cluster 2—Intermediate Light and Single Trailer
Route, Primarily Urban Principal Arterial, Rural
Minor Arterials

4

1.8

4.7

5

14.1

47.2

6

2.7

7.4

7

0.1

0.4

8

7.6

12.4

9

66.8

25.1

10

0.7

1.7

11

4.3

0.6

12

1.4

0.1

13

0.5

0.4

HOURLY TRUCK DISTRIBUTION
Statistical analysis identified three hourly truck distribution clusters in Arizona. Sensitivity
analysis, however, indicated that there was no significant change in pavement design (PCC
thickness, HMA not affected) due to application of the identified hourly distribution clusters.
However, the sensitivity analysis was limited, and it is still recommended that these three
distributions be used as appropriate, as it is the true representation of actual truck loading
throughout the 24-hour period. The recommended hourly distributions are shown in Table 34.

95

Table 34. Recommended MEPDG Hourly Truck Distribution Input for Design in Arizona.
Time of Day,
Hours

Cluster 1—Rural
Highways

Cluster 2—Urban
Highways

Cluster 3—Long Haul
Sections of Rural
Highways

0

1.9

0.9

3.7

1

1.7

0.8

3.4

2

1.6

0.7

2.9

3

1.7

1.0

2.8

4

1.8

2.0

2.6

5

2.3

3.6

2.6

6

3.2

5.5

3.0

7

4.1

6.1

3.2

8

5.0

6.6

3.8

9

5.8

7.0

4.2

10

6.3

7.1

4.5

11

6.6

7.0

4.7

12

6.8

6.8

4.7

13

6.7

6.8

5.0

14

6.6

6.8

5.3

15

6.3

6.3

5.3

16

5.9

5.8

5.4

17

5.4

5.0

5.3

18

4.8

4.1

5.3

19

4.1

3.2

4.9

20

3.6

2.5

4.7

21

3.2

2.0

4.4

22

2.6

1.5

4.4

23

2.2

1.1

4.1

MONTHLY ADJUSTMENT FACTOR
Statistical analysis identified a single cluster for MAF for Arizona. Thus, a sensitivity analysis
was not necessary. The statewide default Arizona MEPDG MAF input recommended for design
is presented in Table 35. Heavier truck traffic in the winter is reflected in these values.

96

Table 35. Recommended MEPDG MAF Input for Design in Arizona.
Month

Statewide Default Monthly Adjustment Factors
VC4

VC5

VC6

VC7

VC8

VC9

VC10

VC11

VC12

VC13

January

0.99

0.87

0.85

1.11

0.90

0.86

1.03

0.69

0.62

1.23

February

1.03

0.97

0.90

0.87

0.94

0.92

0.95

0.78

0.85

0.96

March

1.02

0.99

0.92

0.94

1.02

0.94

0.88

0.85

0.98

0.84

April

0.97

0.91

0.94

1.13

0.92

0.93

0.91

0.81

1.00

0.91

May

0.96

0.95

0.91

0.78

0.92

0.93

0.83

0.97

0.91

0.79

June

0.89

0.96

0.93

0.96

0.93

0.98

1.00

1.13

1.13

0.79

July

0.91

0.98

0.92

0.64

0.91

0.92

0.84

1.13

0.95

1.00

August

0.95

0.99

1.01

0.86

0.93

1.08

0.95

1.25

1.20

0.74

September

1.05

0.95

0.90

0.84

0.90

0.90

0.82

0.96

0.91

0.67

October

1.06

1.01

1.05

1.00

1.08

1.00

0.96

1.00

0.99

1.05

November

1.10

1.24

1.35

1.25

1.40

1.25

1.42

1.14

1.22

1.41

December
1.05 1.19 1.33
1.63
1.14
1.27
1.42
1.30
1.24
1.60
*Winter months (October, November, December, and January) experienced higher levels of truck traffic.

AXLE LOAD DISTRIBUTION
Statistical analysis identified three ALD clusters in Arizona. Sensitivity analysis results were
mixed, showing that ALD could significantly impact both HMA and JPCP design under different
design scenarios. Thus, the application of three ALD clusters for MEPDG pavement design is
recommended. A description of the three ALD clusters is presented in Tables 36 through 47 for
single, tandem, tridem, and quad axles.
AXLES PER TRUCK
Statistical analysis identified a single cluster for axles-per-truck statistics for Arizona. Thus,
sensitivity analysis was not necessary. The single statewide default for axles per truck
recommended for design is presented in Table 48.

97

Table 36. Recommended Cluster 1 Single Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

10

11

12

13

3,000

0.038

0.486

0.000

0.973

4.537

0.210

0.310

0.460

0.271

1.896

4,000

0.050

4.309

0.002

0.325

7.207

0.443

0.102

1.552

1.152

1.431

5,000

0.050

10.099

0.374

0.604

4.568

0.610

0.107

2.697

2.160

1.439

6,000

0.561

24.219

2.839

1.130

12.103

1.374

0.952

4.161

4.024

2.560

7,000

1.186

12.469

3.379

1.569

8.580

1.938

1.709

5.079

6.453

3.890

8,000

2.753

8.969

3.971

2.240

7.778

2.871

3.149

6.035

7.945

4.738

9,000

5.038

7.621

6.495

4.258

8.637

5.029

6.124

7.079

8.436

6.337

10,000

7.637

6.402

10.604

1.845

9.136

9.190

11.881

8.643

9.645

7.880

11,000

9.989

5.215

14.328

9.324

8.390

14.862

17.107

9.816

10.853

10.451

12,000

13.469

4.577

16.163

9.040

7.190

19.357

19.704

9.964

11.722

12.204

13,000

14.165

3.573

13.318

5.189

5.256

17.404

15.820

8.913

10.620

11.182

14,000

12.605

2.770

8.826

10.954

3.797

10.360

9.559

7.502

8.067

8.574

15,000

9.455

2.186

6.182

9.957

2.941

5.397

5.321

6.415

6.276

5.654

16,000

6.763

1.714

4.304

6.482

2.287

3.385

3.034

5.554

4.598

4.316

17,000

4.416

1.347

3.049

7.679

1.877

2.393

1.907

4.641

3.063

3.721

18,000

3.101

1.067

1.991

6.646

1.467

1.745

1.319

3.730

1.884

2.777

19,000

2.432

0.804

1.323

4.462

1.119

1.240

0.695

2.730

1.201

2.466

20,000

1.873

0.601

0.878

3.590

0.816

0.824

0.407

1.917

0.667

2.301

21,000

1.367

0.446

0.650

2.700

0.551

0.514

0.233

1.250

0.362

1.282

22,000

0.944

0.311

0.396

1.885

0.374

0.307

0.122

0.744

0.244

1.167

23,000

0.661

0.207

0.281

2.898

0.259

0.171

0.097

0.462

0.140

0.747

24,000

0.513

0.146

0.205

1.663

0.164

0.099

0.048

0.248

0.095

0.626

25,000

0.296

0.094

0.114

1.586

0.105

0.064

0.038

0.139

0.039

0.521

26,000

0.219

0.064

0.089

1.231

0.059

0.039

0.031

0.079

0.017

0.367

27,000

0.131

0.037

0.056

0.732

0.043

0.026

0.044

0.055

0.016

0.299

28,000

0.118

0.029

0.044

0.280

0.028

0.018

0.026

0.035

0.011

0.166

29,000

0.055

0.026

0.033

0.050

0.020

0.007

0.007

0.020

0.006

0.177

30,000

0.045

0.013

0.014

0.112

0.012

0.003

0.031

0.009

0.000

0.145

31,000

0.015

0.006

0.018

0.125

0.005

0.004

0.005

0.004

0.001

0.063

32,000

0.016

0.007

0.011

0.000

0.003

0.003

0.005

0.005

0.000

0.032

33,000

0.006

0.006

0.005

0.000

0.002

0.002

0.002

0.003

0.000

0.038

34,000

0.004

0.003

0.003

0.308

0.002

0.006

0.007

0.002

0.001

0.032

35,000

0.002

0.004

0.005

0.000

0.001

0.001

0.006

0.002

0.000

0.032

36,000

0.001

0.003

0.001

0.029

0.002

0.001

0.018

0.003

0.000

0.018

37,000

0.009

0.004

0.004

0.000

0.003

0.000

0.004

0.002

0.000

0.023

38,000

0.001

0.002

0.003

0.057

0.001

0.001

0.005

0.000

0.001

0.028

39,000

0.004

0.002

0.004

0.048

0.000

0.001

0.003

0.002

0.000

0.004

40,000

0.004

0.002

0.004

0.019

0.001

0.001

0.000

0.000

0.000

0.007

41,000

0.010

0.002

0.011

0.000

0.002

0.014

0.030

0.000

0.000

0.065

98

Table 37. Recommended Cluster 1 Tandem Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

10

11

12

13

6,000

0.011

0.000

0.290

0.000

5.050

0.141

0.188

0.000

0.111

0.714

8,000

0.011

0.000

4.419

0.000

7.927

0.747

0.636

50.000

0.563

1.083

10,000

0.018

0.000

10.371

0.000

5.991

1.799

1.565

25.000

2.054

2.590

12,000

0.090

0.000

14.419

0.000

8.533

3.519

2.762

0.000

4.427

5.103

14,000

0.301

0.000

13.063

0.000

11.528

5.235

5.318

0.000

8.715

6.632

16,000

0.807

0.000

8.055

0.000

12.541

6.013

6.893

0.000

12.451

6.310

18,000

2.583

0.000

5.543

100.00

11.386

6.240

8.209

0.000

13.291

6.604

20,000

5.417

0.000

4.607

0.000

9.107

6.284

7.922

0.000

14.918

5.181

22,000

9.568

0.000

4.618

0.000

6.941

6.165

8.416

0.000

14.368

5.148

24,000

13.467

0.000

5.081

0.000

5.326

6.388

8.015

0.000

12.356

4.560

26,000

15.595

0.000

5.359

0.000

3.988

6.667

7.735

0.000

8.337

4.293

28,000

15.288

0.000

5.137

0.000

2.989

7.087

7.740

0.000

4.441

4.377

30,000

12.411

0.000

4.544

0.000

2.190

7.796

7.462

0.000

1.967

4.153

32,000

9.015

0.000

3.866

0.000

1.772

8.362

6.391

0.000

1.000

4.583

34,000

6.407

0.000

2.885

0.000

1.256

8.232

5.366

0.000

0.377

5.106

36,000

3.582

0.000

2.296

0.000

0.956

7.160

4.827

25.000

0.182

5.626

38,000

1.935

0.000

1.705

0.000

0.777

5.210

3.127

0.000

0.137

5.551

40,000

1.306

0.000

1.188

0.000

0.501

3.086

2.436

0.000

0.068

4.950

42,000

0.738

0.000

0.866

0.000

0.303

1.683

1.647

0.000

0.036

4.187

44,000

0.503

0.000

0.552

0.000

0.218

0.895

1.096

0.000

0.019

3.269

46,000

0.377

0.000

0.435

0.000

0.098

0.514

0.774

0.000

0.006

2.382

48,000

0.212

0.000

0.244

0.000

0.170

0.302

0.432

0.000

0.011

1.809

50,000

0.138

0.000

0.140

0.000

0.037

0.174

0.326

0.000

0.030

1.453

52,000

0.065

0.000

0.102

0.000

0.020

0.101

0.164

0.000

0.000

1.050

54,000

0.045

0.000

0.053

0.000

0.009

0.059

0.172

0.000

0.000

0.820

56,000

0.027

0.000

0.035

0.000

0.006

0.034

0.116

0.000

0.000

0.627

58,000

0.022

0.000

0.024

0.000

0.011

0.016

0.060

0.000

0.010

0.514

60,000

0.010

0.000

0.019

0.000

0.004

0.006

0.036

0.000

0.005

0.305

62,000

0.007

0.000

0.014

0.000

0.003

0.004

0.026

0.000

0.000

0.269

64,000

0.011

0.000

0.009

0.000

0.001

0.002

0.065

0.000

0.095

0.194

66,000

0.001

0.000

0.004

0.000

0.001

0.001

0.018

0.000

0.000

0.122

68,000

0.003

0.000

0.005

0.000

0.001

0.001

0.015

0.000

0.000

0.106

70,000

0.003

0.000

0.003

0.000

0.001

0.000

0.011

0.000

0.000

0.111

72,000

0.001

0.000

0.002

0.000

0.000

0.000

0.001

0.000

0.000

0.062

74,000

0.000

0.000

0.007

0.000

0.000

0.000

0.002

0.000

0.000

0.076

76,000

0.000

0.000

0.002

0.000

0.000

0.000

0.001

0.000

0.000

0.039

78,000

0.000

0.000

0.001

0.000

0.000

0.000

0.001

0.000

0.000

0.024

80,000

0.000

0.000

0.002

0.000

0.000

0.000

0.004

0.000

0.000

0.010

82,000

0.000

0.000

0.000

0.000

0.000

0.000

0.005

0.000

0.000

0.003

99

Table 38. Recommended Cluster 1 Tridem Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

12,000

0.000

0.000

0.000

0.407

0.000

15,000

0.000

0.000

0.000

0.394

18,000

0.000

0.000

0.000

5.444

21,000

0.000

0.000

0.000

24,000

0.000

0.000

0.000

27,000

0.000

0.000

30,000

0.000

0.000

33,000

0.000

36,000

0.000

39,000

10

11

12

13

0.105

0.735

0.000

3.111

0.594

0.000

1.295

2.336

0.000

3.842

1.000

0.000

33.438

6.388

0.000

7.616

1.431

5.957

0.000

12.495

9.254

0.000

9.580

2.955

5.374

0.000

9.010

9.670

0.000

20.038

3.998

0.000

3.184

0.000

5.533

8.246

0.000

13.931

4.515

0.000

3.707

0.000

1.862

6.863

0.000

16.044

5.753

0.000

0.000

3.412

0.000

1.067

7.361

0.000

1.338

3.861

0.000

0.000

6.737

0.000

1.571

7.440

0.000

1.418

4.878

0.000

0.000

0.000

6.619

0.000

1.510

7.897

0.000

8.847

6.155

42,000

0.000

0.000

0.000

11.794

0.000

1.286

8.187

0.000

0.236

6.803

45,000

0.000

0.000

0.000

9.811

0.000

0.410

7.334

0.000

0.342

6.066

48,000

0.000

0.000

0.000

11.127

0.000

0.614

5.520

0.000

1.453

6.879

51,000

0.000

0.000

0.000

7.935

0.000

4.971

3.890

0.000

3.549

7.441

54,000

0.000

0.000

0.000

5.380

0.000

2.495

2.809

0.000

1.596

11.680

57,000

0.000

0.000

0.000

3.377

0.000

5.429

2.036

0.000

2.471

5.717

60,000

0.000

0.000

0.000

3.084

0.000

4.762

1.670

0.000

1.111

6.126

63,000

0.000

0.000

0.000

3.335

0.000

2.381

0.817

0.000

2.458

4.731

66,000

0.000

0.000

0.000

2.002

0.000

0.000

0.552

0.000

0.000

3.632

69,000

0.000

0.000

0.000

0.483

0.000

9.524

0.395

0.000

0.513

2.345

72,000

0.000

0.000

0.000

0.121

0.000

0.000

0.250

0.000

0.000

0.801

75,000

0.000

0.000

0.000

0.300

0.000

0.000

0.126

0.000

0.000

0.972

78,000

0.000

0.000

0.000

0.000

0.000

0.000

0.074

0.000

0.000

1.026

81,000

0.000

0.000

0.000

0.000

0.000

0.000

0.055

0.000

0.000

0.211

84,000

0.000

0.000

0.000

0.000

0.000

0.000

0.026

0.000

0.000

0.218

87,000

0.000

0.000

0.000

0.000

0.000

0.000

0.021

0.000

0.000

0.016

90,000

0.000

0.000

0.000

0.000

0.000

0.000

0.009

0.000

0.000

0.037

93,000

0.000

0.000

0.000

0.000

0.000

0.000

0.004

0.000

0.513

0.017

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.002

0.000

0.000

0.011

99,000

0.000

0.000

0.000

0.000

0.000

0.000

0.001

0.000

0.000

0.005

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.001

0.000

0.000

0.000

100

Table 39. Recommended Cluster 1 Quad Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

10

11

12

13

12,000

0.000

0.000

0.000

0.000

0.000

0.000

0.541

0.000

0.000

0.335

15,000

0.000

0.000

0.000

0.000

0.000

7.000

0.312

0.000

1.753

0.329

18,000

0.000

0.000

0.000

0.280

0.000

2.000

2.297

0.000

0.000

1.589

21,000

0.000

0.000

0.000

0.280

0.000

15.375

3.921

0.000

10.526

4.071

24,000

0.000

0.000

0.000

0.820

0.000

3.440

5.838

0.000

10.526

6.419

27,000

0.000

0.000

0.000

10.000

0.000

8.215

1.241

0.000

1.753

6.580

30,000

0.000

0.000

0.000

0.000

0.000

10.000

0.376

0.000

1.753

3.973

33,000

0.000

0.000

0.000

1.060

0.000

5.625

1.515

0.000

5.263

6.529

36,000

0.000

0.000

0.000

0.280

0.000

0.000

4.541

0.000

0.000

5.374

39,000

0.000

0.000

0.000

0.540

0.000

0.000

6.162

0.000

12.016

9.536

42,000

0.000

0.000

0.000

11.260

0.000

0.000

5.503

0.000

2.295

8.463

45,000

0.000

0.000

0.000

14.200

0.000

0.000

12.556

0.000

4.874

7.089

48,000

0.000

0.000

0.000

4.140

0.000

0.000

10.197

0.000

5.668

6.515

51,000

0.000

0.000

0.000

14.600

0.000

10.000

9.732

0.000

13.868

4.971

54,000

0.000

0.000

0.000

11.700

0.000

0.000

8.729

0.000

15.579

4.699

57,000

0.000

0.000

0.000

21.360

0.000

0.000

8.024

0.000

7.979

5.794

60,000

0.000

0.000

0.000

3.640

0.000

0.625

3.126

0.000

3.958

2.460

63,000

0.000

0.000

0.000

3.520

0.000

10.000

3.159

0.000

1.363

2.749

66,000

0.000

0.000

0.000

1.840

0.000

0.000

2.935

0.000

0.532

1.945

69,000

0.000

0.000

0.000

0.540

0.000

0.000

3.038

0.000

0.000

1.293

72,000

0.000

0.000

0.000

0.000

0.000

0.000

0.544

0.000

0.274

1.304

75,000

0.000

0.000

0.000

0.000

0.000

0.000

0.450

0.000

0.000

1.224

78,000

0.000

0.000

0.000

0.000

0.000

0.000

2.382

0.000

0.000

1.979

81,000

0.000

0.000

0.000

0.000

0.000

15.000

0.000

0.000

0.000

1.696

84,000

0.000

0.000

0.000

0.000

0.000

0.000

0.121

0.000

0.000

1.705

87,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.234

90,000

0.000

0.000

0.000

0.000

0.000

7.500

0.782

0.000

0.000

0.406

93,000

0.000

0.000

0.000

0.000

0.000

0.000

1.471

0.000

0.000

0.061

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.036

99,000

0.000

0.000

0.000

0.000

0.000

2.500

0.000

0.000

0.000

0.001

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

101

Table 40. Recommended Cluster 2 Single Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

10

11

12

13

3,000

0.000

0.483

0.003

0.000

1.870

0.327

0.110

1.197

0.547

2.010

4,000

0.003

5.240

0.007

0.130

4.660

1.167

0.203

4.313

2.613

1.910

5,000

0.000

6.467

0.013

0.377

3.513

1.820

0.347

6.103

4.260

1.053

6,000

0.813

24.707

1.520

0.343

9.947

2.287

1.103

6.173

5.973

1.743

7,000

2.597

12.997

2.213

1.303

8.213

2.587

2.640

6.763

8.160

2.820

8,000

5.853

9.477

3.910

1.437

9.240

4.280

5.057

7.827

9.503

4.083

9,000

9.740

7.770

7.057

2.677

10.167

8.300

9.987

8.813

11.223

7.913

10,000

10.473

6.267

10.717

4.523

9.520

12.957

13.567

8.070

10.720

11.610

11,000

10.533

5.100

12.917

10.240

8.227

15.793

16.677

6.693

9.950

12.047

12,000

10.333

4.387

13.483

5.933

7.130

16.363

17.030

5.870

9.523

11.620

13,000

8.970

3.577

11.367

7.757

5.573

12.140

11.493

5.030

7.123

9.320

14,000

7.987

2.790

8.947

9.630

4.357

7.240

8.203

4.840

5.310

7.103

15,000

6.293

2.270

7.070

8.387

3.700

4.337

4.417

4.787

4.083

4.960

16,000

5.657

1.857

5.527

6.800

3.067

2.937

3.197

4.830

2.797

4.430

17,000

4.760

1.473

4.087

8.147

2.543

2.107

1.650

4.370

2.287

3.303

18,000

3.880

1.240

3.173

6.060

2.010

1.587

0.997

3.840

1.537

2.713

19,000

3.613

0.940

2.177

5.787

1.557

1.143

0.993

2.983

1.280

2.183

20,000

2.513

0.757

1.810

4.810

1.213

0.860

0.850

2.310

1.030

1.830

21,000

1.903

0.557

1.357

3.797

0.913

0.603

0.447

1.560

0.607

2.127

22,000

1.477

0.423

0.830

7.473

0.657

0.367

0.390

1.087

0.503

0.940

23,000

0.833

0.303

0.583

1.657

0.473

0.243

0.217

0.747

0.297

1.150

24,000

0.763

0.230

0.333

0.977

0.343

0.150

0.133

0.527

0.137

0.530

25,000

0.373

0.187

0.210

0.467

0.217

0.097

0.060

0.333

0.097

0.417

26,000

0.277

0.113

0.163

0.213

0.157

0.073

0.090

0.263

0.097

0.410

27,000

0.150

0.060

0.083

0.203

0.120

0.047

0.083

0.183

0.060

0.263

28,000

0.070

0.040

0.087

0.517

0.077

0.033

0.010

0.103

0.050

0.140

29,000

0.027

0.027

0.090

0.160

0.067

0.017

0.013

0.080

0.040

0.093

30,000

0.030

0.023

0.020

0.017

0.030

0.013

0.003

0.067

0.020

0.137

31,000

0.013

0.017

0.033

0.153

0.020

0.003

0.007

0.043

0.020

0.123

32,000

0.010

0.010

0.040

0.007

0.020

0.003

0.000

0.033

0.017

0.033

33,000

0.003

0.010

0.027

0.053

0.007

0.003

0.000

0.023

0.013

0.100

34,000

0.003

0.003

0.013

0.000

0.007

0.003

0.000

0.020

0.010

0.017

35,000

0.023

0.003

0.003

0.000

0.013

0.003

0.017

0.010

0.017

0.013

36,000

0.000

0.003

0.010

0.003

0.003

0.003

0.003

0.013

0.007

0.037

37,000

0.003

0.007

0.023

0.000

0.003

0.003

0.027

0.010

0.007

0.017

38,000

0.000

0.003

0.020

0.000

0.003

0.003

0.000

0.007

0.010

0.010

39,000

0.000

0.003

0.007

0.000

0.003

0.003

0.003

0.007

0.010

0.007

40,000

0.000

0.003

0.023

0.000

0.003

0.000

0.000

0.007

0.003

0.003

41,000

0.003

0.003

0.007

0.000

0.003

0.003

0.000

0.003

0.003

0.000

102

Table 41. Recommended Cluster 2 Tandem Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

10

11

12

13

6,000

0.000

0.000

0.487

0.000

1.720

0.340

0.230

0.000

0.070

0.253

8,000

0.017

0.000

4.410

0.000

7.433

2.333

1.273

0.000

1.070

1.060

10,000

0.090

0.000

6.453

0.000

6.467

5.373

2.423

0.000

3.877

3.793

12,000

0.373

0.000

7.197

0.000

9.687

7.783

6.507

0.000

9.180

7.917

14,000

0.807

0.000

7.500

0.000

10.947

8.717

8.117

0.000

16.933

10.177

16,000

1.670

0.000

7.300

0.000

10.387

8.217

9.567

0.000

17.207

8.763

18,000

3.877

0.000

6.697

0.000

8.320

7.120

9.403

0.000

15.760

6.820

20,000

10.083

0.000

6.373

0.000

7.063

6.110

8.683

0.000

11.910

4.950

22,000

11.833

0.000

6.150

0.000

5.307

5.460

7.567

0.000

6.963

3.857

24,000

14.067

0.000

6.410

0.000

4.727

5.593

6.893

0.000

6.037

4.053

26,000

14.563

0.000

6.407

0.000

4.270

5.863

5.847

0.000

4.307

4.277

28,000

11.913

0.000

6.173

0.000

3.900

6.240

5.907

0.000

2.640

4.203

30,000

9.687

0.000

5.530

0.000

3.847

6.450

4.920

0.000

1.177

4.330

32,000

6.043

0.000

4.713

0.000

3.463

6.103

4.453

0.000

0.970

4.870

34,000

4.753

0.000

3.990

0.000

2.957

5.213

4.053

0.000

0.517

4.533

36,000

3.437

0.000

3.450

0.000

2.517

4.003

2.590

0.000

0.343

3.907

38,000

2.640

0.000

2.653

0.000

1.957

2.857

2.283

0.000

0.337

3.527

40,000

1.833

0.000

2.250

0.000

1.353

1.967

2.227

0.000

0.130

3.023

42,000

0.940

0.000

1.793

0.000

0.980

1.323

1.940

0.000

0.120

2.593

44,000

0.527

0.000

1.103

0.000

0.787

0.907

1.417

0.000

0.067

2.447

46,000

0.273

0.000

0.810

0.000

0.587

0.610

1.073

0.000

0.063

1.883

48,000

0.247

0.000

0.707

0.000

0.347

0.410

0.717

0.000

0.050

1.550

50,000

0.133

0.000

0.413

0.000

0.253

0.290

0.447

0.000

0.043

1.553

52,000

0.080

0.000

0.287

0.000

0.143

0.183

0.473

0.000

0.077

1.013

54,000

0.080

0.000

0.223

0.000

0.097

0.123

0.327

0.000

0.023

1.100

56,000

0.037

0.000

0.133

0.000

0.057

0.077

0.227

0.000

0.023

0.713

58,000

0.013

0.000

0.093

0.000

0.033

0.060

0.110

0.000

0.027

0.713

60,000

0.003

0.000

0.073

0.000

0.013

0.040

0.143

0.000

0.030

0.437

62,000

0.003

0.000

0.040

0.000

0.017

0.023

0.077

0.000

0.017

0.493

64,000

0.003

0.000

0.030

0.000

0.017

0.020

0.063

0.000

0.020

0.320

66,000

0.000

0.000

0.027

0.000

0.013

0.017

0.020

0.000

0.017

0.257

68,000

0.000

0.000

0.003

0.000

0.003

0.013

0.010

0.000

0.013

0.163

70,000

0.000

0.000

0.013

0.000

0.007

0.010

0.007

0.000

0.003

0.107

72,000

0.000

0.000

0.013

0.000

0.000

0.007

0.003

0.000

0.000

0.107

74,000

0.000

0.000

0.017

0.000

0.000

0.007

0.000

0.000

0.000

0.083

76,000

0.000

0.000

0.000

0.000

0.000

0.007

0.000

0.000

0.000

0.043

78,000

0.000

0.000

0.000

0.000

0.000

0.003

0.000

0.000

0.000

0.020

80,000

0.000

0.000

0.003

0.000

0.000

0.000

0.000

0.000

0.000

0.023

82,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.003

0.010

103

Table 42. Recommended Cluster 2 Tridem Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

12,000

0.000

0.000

0.000

0.000

0.000

15,000

0.000

0.000

0.000

0.017

0.000

18,000

0.000

0.000

0.000

4.223

0.000

21,000

0.000

0.000

0.000

0.313

0.000

24,000

0.000

0.000

0.000

2.490

0.000

27,000

0.000

0.000

0.000

3.347

30,000

0.000

0.000

0.000

1.907

33,000

0.000

0.000

0.000

36,000

0.000

0.000

0.000

39,000

0.000

0.000

42,000

0.000

45,000

0.000

48,000
51,000

10

11

12

13

1.187

0.000

0.000

0.177

0.000

4.453

0.000

7.288

2.030

66.667

13.067

0.000

14.169

3.180

0.000

9.680

0.000

14.750

4.303

0.044

7.483

0.000

19.200

3.123

0.000

0.133

7.557

0.000

10.631

3.933

0.000

1.167

5.907

0.000

0.000

1.653

3.587

0.000

2.456

7.013

0.000

8.506

3.487

7.653

0.000

1.533

6.147

0.000

0.675

2.563

0.000

7.900

0.000

1.589

5.463

0.000

3.300

3.720

0.000

0.000

10.507

0.000

3.222

6.010

0.000

1.550

5.807

0.000

0.000

11.580

0.000

2.678

5.750

0.000

0.694

6.150

0.000

0.000

0.000

18.143

0.000

1.856

4.740

0.000

2.938

9.500

0.000

0.000

0.000

7.083

0.000

4.867

4.057

0.000

4.469

7.980

54,000

0.000

0.000

0.000

6.513

0.000

12.056

2.977

0.000

0.694

6.273

57,000

0.000

0.000

0.000

4.247

0.000

1.511

2.370

0.000

10.775

4.353

60,000

0.000

0.000

0.000

6.077

0.000

0.089

1.907

0.000

0.175

7.800

63,000

0.000

0.000

0.000

2.560

0.000

0.044

1.407

0.000

0.175

2.747

66,000

0.000

0.000

0.000

0.727

0.000

0.011

0.860

0.000

0.000

6.403

69,000

0.000

0.000

0.000

0.347

0.000

0.022

0.690

0.000

0.000

3.793

72,000

0.000

0.000

0.000

0.487

0.000

0.022

0.360

0.000

0.000

2.597

75,000

0.000

0.000

0.000

0.050

0.000

0.011

0.260

0.000

0.000

1.513

78,000

0.000

0.000

0.000

0.090

0.000

0.000

0.337

0.000

0.000

0.807

81,000

0.000

0.000

0.000

0.007

0.000

0.000

0.113

0.000

0.000

1.097

84,000

0.000

0.000

0.000

0.120

0.000

0.000

0.077

0.000

0.000

0.230

87,000

0.000

0.000

0.000

0.007

0.000

0.000

0.057

0.000

0.000

0.257

90,000

0.000

0.000

0.000

0.013

0.000

0.000

0.013

0.000

0.000

0.140

93,000

0.000

0.000

0.000

0.000

0.000

0.000

0.040

0.000

0.000

0.440

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.020

0.000

0.000

0.000

99,000

0.000

0.000

0.000

0.003

0.000

0.000

0.007

0.000

0.000

3.793

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.050

104

0.000

Table 43. Recommended Cluster 2 Quad Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

10

11

12

13

12,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.015

15,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.815

18,000

0.000

0.000

0.000

0.200

0.000

0.000

0.219

0.000

0.000

7.326

21,000

0.000

0.000

0.000

0.200

0.000

6.660

0.971

0.000

0.000

4.178

24,000

0.000

0.000

0.000

0.200

0.000

20.000

0.300

0.000

0.000

4.859

27,000

0.000

0.000

0.000

0.200

0.000

0.000

1.181

0.000

2.100

7.944

30,000

0.000

0.000

0.000

0.900

0.000

0.000

0.900

0.000

0.150

7.719

33,000

0.000

0.000

0.000

1.800

0.000

0.000

1.290

0.000

0.975

5.319

36,000

0.000

0.000

0.000

6.400

0.000

0.000

4.143

0.000

0.850

5.889

39,000

0.000

0.000

0.000

14.800

0.000

0.000

5.643

0.000

9.200

9.563

42,000

0.000

0.000

0.000

10.100

0.000

20.000

4.186

0.000

8.450

6.207

45,000

0.000

0.000

0.000

10.700

0.000

0.000

4.833

0.000

21.325

6.700

48,000

0.000

0.000

0.000

7.500

0.000

0.000

6.957

0.000

7.575

6.852

51,000

0.000

0.000

0.000

8.500

0.000

0.000

8.538

0.000

12.950

3.856

54,000

0.000

0.000

0.000

8.900

0.000

0.000

10.014

0.000

5.850

2.256

57,000

0.000

0.000

0.000

8.200

0.000

0.000

5.162

0.000

10.600

2.533

60,000

0.000

0.000

0.000

6.900

0.000

10.000

5.519

0.000

14.250

1.496

63,000

0.000

0.000

0.000

4.800

0.000

0.000

7.162

0.000

4.025

1.278

66,000

0.000

0.000

0.000

2.400

0.000

0.000

4.652

0.000

0.775

1.756

69,000

0.000

0.000

0.000

2.800

0.000

0.000

8.062

0.000

0.125

5.426

72,000

0.000

0.000

0.000

0.800

0.000

6.660

1.567

0.000

0.525

0.381

75,000

0.000

0.000

0.000

1.700

0.000

0.000

0.943

0.000

0.050

0.763

78,000

0.000

0.000

0.000

0.500

0.000

0.000

5.576

0.000

0.025

0.859

81,000

0.000

0.000

0.000

0.700

0.000

30.000

1.257

0.000

0.025

1.219

84,000

0.000

0.000

0.000

0.000

0.000

0.000

9.800

0.000

0.025

0.493

87,000

0.000

0.000

0.000

0.100

0.000

0.000

0.343

0.000

0.050

1.815

90,000

0.000

0.000

0.000

0.200

0.000

6.660

0.057

0.000

0.025

0.078

93,000

0.000

0.000

0.000

0.200

0.000

0.000

0.067

0.000

0.000

1.107

96,000

0.000

0.000

0.000

0.200

0.000

0.000

0.133

0.000

0.000

0.496

99,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.330

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.529

0.000

0.000

0.470

105

Table 44. Recommended Cluster 3 Single Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

10

11

12

13

3,000

0.003

0.883

0.000

0.268

7.963

0.403

0.215

0.458

0.173

0.348

4,000

0.000

6.158

0.000

3.246

12.843

0.993

0.053

0.993

0.468

0.765

5,000

0.005

33.240

0.420

0.251

9.020

1.703

0.118

2.935

1.208

1.635

6,000

0.078

25.343

3.210

1.284

11.650

2.588

0.370

2.500

3.103

3.095

7,000

0.235

8.685

5.378

3.576

8.488

1.403

0.540

5.060

9.008

12.428

8,000

1.083

5.198

2.755

5.981

6.773

1.435

0.825

4.350

7.508

14.968

9,000

1.465

4.983

2.673

2.530

6.020

2.550

1.690

5.795

7.558

5.345

10,000

2.310

4.010

4.870

5.332

5.710

5.595

5.570

8.723

7.918

5.715

11,000

4.288

3.025

11.203

4.830

5.978

9.620

16.163

11.168

11.265

14.053

12,000

7.043

2.248

16.895

8.141

5.313

21.498

27.958

8.678

15.065

14.655

13,000

12.550

1.538

16.353

14.792

4.295

24.273

25.995

5.653

11.558

8.393

14,000

21.823

1.143

14.953

16.403

3.025

7.993

10.668

5.115

6.730

4.933

15,000

25.410

0.890

9.360

3.327

2.118

2.548

3.368

5.235

6.960

2.445

16,000

14.423

0.660

4.123

2.741

1.685

2.190

2.438

6.020

4.200

3.035

17,000

5.383

0.513

2.115

12.332

1.370

3.025

1.868

6.408

3.088

1.503

18,000

1.698

0.453

2.020

3.022

1.228

4.368

0.598

6.413

1.653

1.535

19,000

0.710

0.340

1.573

1.519

1.065

3.920

0.308

5.008

1.188

1.785

20,000

0.495

0.225

0.935

2.976

0.925

2.398

0.008

5.458

0.665

0.873

21,000

0.338

0.170

0.430

1.751

0.658

0.960

0.000

2.548

0.528

0.638

22,000

0.195

0.105

0.333

3.341

0.403

0.328

0.000

0.830

0.045

0.218

23,000

0.155

0.063

0.153

0.043

0.208

0.078

1.278

0.288

0.020

0.188

24,000

0.145

0.028

0.023

0.132

0.128

0.005

0.000

0.183

0.000

0.153

25,000

0.083

0.013

0.020

0.000

0.018

0.005

0.000

0.028

0.000

0.068

26,000

0.033

0.005

0.050

0.314

0.013

0.003

0.000

0.010

0.005

0.038

27,000

0.020

0.000

0.033

0.014

0.003

0.000

0.000

0.030

0.005

0.088

28,000

0.005

0.000

0.000

0.000

0.003

0.000

0.000

0.010

0.000

0.033

29,000

0.003

0.000

0.025

0.000

0.003

0.000

0.000

0.003

0.000

0.000

30,000

0.000

0.000

0.020

0.000

0.003

0.000

0.000

0.010

0.000

0.000

31,000

0.000

0.000

0.008

0.000

0.000

0.000

0.000

0.003

0.000

0.000

32,000

0.003

0.000

0.000

0.000

0.003

0.000

0.000

0.003

0.000

0.000

33,000

0.008

0.000

0.008

0.000

0.000

0.000

0.000

0.003

0.000

0.005

34,000

0.003

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

35,000

0.000

0.000

0.003

0.924

0.000

0.000

0.000

0.003

0.000

0.000

36,000

0.008

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

37,000

0.000

0.000

0.015

0.000

0.000

0.000

0.000

0.000

0.000

0.000

38,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

39,000

0.000

0.000

0.000

0.700

0.000

0.000

0.000

0.000

0.000

0.000

40,000

0.000

0.000

0.008

0.000

0.000

0.000

0.000

0.000

0.000

0.020

41,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

106

Table 45. Recommended Cluster 3 Tandem Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

10

11

12

13

6,000

0.000

0.000

0.013

0.000

14.135

0.078

0.168

0.000

0.000

0.165

8,000

0.000

0.000

0.275

0.000

7.453

0.525

0.220

0.000

0.015

0.795

10,000

0.023

0.000

3.400

0.000

2.855

2.173

0.415

0.000

0.108

2.188

12,000

0.035

0.000

12.353

0.000

4.743

3.555

0.808

0.000

0.368

15.225

14,000

0.073

0.000

7.678

0.000

9.233

4.945

2.640

0.000

9.020

19.918

16,000

0.173

0.000

7.775

0.000

12.365

5.000

5.895

0.000

8.268

12.485

18,000

0.468

0.000

6.498

0.000

10.983

4.555

8.575

0.000

12.258

5.343

20,000

0.450

0.000

4.740

0.000

8.248

4.443

10.300

0.000

15.963

4.453

22,000

2.275

0.000

3.103

0.000

6.398

4.583

8.048

0.000

17.083

3.888

24,000

4.103

0.000

2.650

0.000

4.850

4.690

5.968

0.000

14.728

2.725

26,000

7.488

0.000

3.558

0.000

2.983

4.663

6.428

0.000

10.870

2.795

28,000

12.265

0.000

7.030

0.000

1.800

4.943

7.815

0.000

8.008

2.058

30,000

16.505

0.000

9.960

0.000

1.468

5.450

7.990

0.000

1.900

3.215

32,000

20.985

0.000

9.523

0.000

1.505

7.398

6.708

0.000

0.930

2.915

34,000

21.285

0.000

7.458

0.000

2.043

11.720

6.898

0.000

0.058

4.153

36,000

11.315

0.000

5.953

0.000

2.935

15.453

6.535

0.000

0.015

3.065

38,000

2.223

0.000

3.580

0.000

2.335

10.035

3.970

0.000

0.015

4.400

40,000

0.203

0.000

1.850

0.000

0.945

3.743

2.598

0.000

0.000

2.315

42,000

0.083

0.000

0.940

0.000

0.355

1.373

1.305

0.000

0.000

1.933

44,000

0.005

0.000

0.623

0.000

0.150

0.420

1.058

0.000

0.000

1.420

46,000

0.003

0.000

0.438

0.000

0.148

0.138

0.820

0.000

0.000

1.088

48,000

0.000

0.000

0.193

0.000

0.095

0.063

1.008

0.000

0.000

1.358

50,000

0.000

0.000

0.120

0.000

0.050

0.030

2.068

0.000

0.000

0.510

52,000

0.000

0.000

0.068

0.000

0.015

0.020

0.688

0.000

0.000

0.345

54,000

0.000

0.000

0.038

0.000

0.010

0.003

0.305

0.000

0.000

0.240

56,000

0.000

0.000

0.060

0.000

0.010

0.003

0.245

0.000

0.000

0.240

58,000

0.000

0.000

0.030

0.000

0.000

0.000

0.068

0.000

0.000

0.058

60,000

0.000

0.000

0.013

0.000

0.000

0.000

0.038

0.000

0.000

0.053

62,000

0.000

0.000

0.013

0.000

0.000

0.000

0.158

0.000

0.000

0.128

64,000

0.000

0.000

0.003

0.000

0.000

0.000

0.058

0.000

0.000

0.150

66,000

0.000

0.000

0.000

0.000

0.000

0.000

0.120

0.000

0.000

0.008

68,000

0.000

0.000

0.005

0.000

0.000

0.000

0.053

0.000

0.000

0.120

70,000

0.000

0.000

0.008

0.000

0.000

0.000

0.013

0.000

0.000

0.010

72,000

0.000

0.000

0.020

0.000

0.000

0.000

0.053

0.000

0.000

0.045

74,000

0.000

0.000

0.000

0.000

0.000

0.000

0.013

0.000

0.000

0.015

76,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.015

78,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

80,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

82,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

107

Table 46. Recommended Cluster 3 Tridem Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

10

11

12

13

12,000

0.000

0.000

0.000

0.000

0.000

0.000

0.255

0.000

0.000

0.000

15,000

0.000

0.000

0.000

1.150

0.000

12.500

1.263

0.000

0.000

1.538

18,000

0.000

0.000

0.000

1.469

0.000

37.500

5.300

0.000

0.000

7.590

21,000

0.000

0.000

0.000

9.369

0.000

25.000

10.040

0.000

100.00

3.959

24,000

0.000

0.000

0.000

2.053

0.000

0.000

9.265

0.000

0.000

5.608

27,000

0.000

0.000

0.000

0.900

0.000

0.000

5.265

0.000

0.000

4.515

30,000

0.000

0.000

0.000

4.103

0.000

0.000

4.885

0.000

0.000

3.510

33,000

0.000

0.000

0.000

3.050

0.000

0.000

5.705

0.000

0.000

2.749

36,000

0.000

0.000

0.000

2.456

0.000

0.000

5.735

0.000

0.000

1.744

39,000

0.000

0.000

0.000

3.416

0.000

0.000

8.415

0.000

0.000

5.064

42,000

0.000

0.000

0.000

3.919

0.000

0.000

11.255

0.000

0.000

3.208

45,000

0.000

0.000

0.000

7.731

0.000

0.000

10.195

0.000

0.000

9.064

48,000

0.000

0.000

0.000

17.606

0.000

25.000

6.675

0.000

0.000

1.354

51,000

0.000

0.000

0.000

29.588

0.000

0.000

5.960

0.000

0.000

4.972

54,000

0.000

0.000

0.000

3.447

0.000

0.000

3.125

0.000

0.000

8.874

57,000

0.000

0.000

0.000

2.147

0.000

0.000

2.398

0.000

0.000

4.369

60,000

0.000

0.000

0.000

0.963

0.000

0.000

1.388

0.000

0.000

3.610

63,000

0.000

0.000

0.000

4.616

0.000

0.000

2.158

0.000

0.000

3.728

66,000

0.000

0.000

0.000

0.000

0.000

0.000

0.153

0.000

0.000

8.741

69,000

0.000

0.000

0.000

0.863

0.000

0.000

0.118

0.000

0.000

4.113

72,000

0.000

0.000

0.000

0.000

0.000

0.000

0.020

0.000

0.000

8.659

75,000

0.000

0.000

0.000

0.000

0.000

0.000

0.030

0.000

0.000

1.236

78,000

0.000

0.000

0.000

0.000

0.000

0.000

0.265

0.000

0.000

0.000

81,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

84,000

0.000

0.000

0.000

0.000

0.000

0.000

0.078

0.000

0.000

0.000

87,000

0.000

0.000

0.000

0.000

0.000

0.000

0.043

0.000

0.000

0.269

90,000

0.000

0.000

0.000

0.000

0.000

0.000

0.033

0.000

0.000

0.000

93,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.256

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.454

99,000

0.000

0.000

0.000

1.150

0.000

0.000

0.000

0.000

0.000

0.000

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

108

Table 47. Recommended Cluster 3 Quad Axle MEPDG ALD Input
for Design in Arizona.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

12,000

0.000

0.000

0.000

0.000

0.000

15,000

0.000

0.000

0.000

0.000

18,000

0.000

0.000

0.000

0.000

21,000

0.000

0.000

0.000

24,000

0.000

0.000

27,000

0.000

0.000

30,000

0.000

33,000

0.000

36,000
39,000

10

11

12

13

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

100.00

0.000

0.000

0.000

1.777

0.000

0.000

0.000

0.000

0.000

0.000

7.517

0.000

0.000

0.000

0.000

0.000

0.000

0.000

15.687

0.000

0.000

0.000

0.000

0.000

0.000

0.000

9.017

0.000

0.000

0.000

0.000

0.000

0.000

0.000

100.00

4.937

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

1.967

0.000

0.000

0.000

0.000

0.000

0.000

83.333

0.000

0.000

0.930

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

9.200

42,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

5.830

45,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

13.100

48,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

2.867

51,000

0.000

0.000

0.000

7.700

0.000

0.000

0.000

0.000

0.000

5.993

54,000

0.000

0.000

0.000

11.550

0.000

0.000

0.000

0.000

0.000

2.927

57,000

0.000

0.000

0.000

36.650

0.000

0.000

0.000

0.000

0.000

6.670

60,000

0.000

0.000

0.000

32.400

0.000

0.000

0.000

0.000

0.000

0.830

63,000

0.000

0.000

0.000

11.750

0.000

0.000

0.000

0.000

0.000

0.647

66,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.450

69,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

72,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.450

75,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

78,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.327

81,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.197

84,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

87,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

90,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

93,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.457

99,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.130

102,000

0.000

0.000

0.000

0.000

0.000

0.000

16.667

0.000

0.000

8.104

109

Table 48. Recommended MEPDG Axles-per-Truck Statistics Default Input
for Design in Arizona.
Vehicle Class
4
5
6
7
8
9
10
11
12
13

Single
1.34
2.14
0.95
0.33
2.61
1.20
0.98
4.78
3.88
1.29

Axle Type
Tandem
Tridem
0.75
0.00
0.00
0.00
0.95
0.00
0.02
0.26
0.49
0.00
1.84
0.00
1.01
0.86
0.00
0.00
0.98
0.03
1.90
0.19

Quad
0.00
0.00
0.00
0.07
0.00
0.00
0.06
0.00
0.14
0.14

LATERAL WANDER OF TRUCKS WITHIN LANE
As vehicles drive down the traffic lane, they wander from side to side in normal driving. This
lateral wander creates fewer full load repetitions for some locations and more repetitions for
other locations. This distribution of lateral wander has been established to be normal and is
defined as follows:
Lateral Offset: Mean distance from the outer paint stripe to the outer edge of the wheel,
in inches.
Standard Deviation: Lateral variation of trucks within the lane, in inches. A normal
distribution was assumed based on previous measurements.
Both the mean lateral offset and the standard deviation have been shown to be significant
MEPDG inputs. They both affect the cracking and joint faulting of JPCP and the lateral standard
deviation affects wheel path rutting for HMA pavements. Lateral truck wander was measured at
four sites in Arizona, as shown in Figure 77. A summary of the data assembled and the computed
MEPDG inputs are presented in Figure 78.

110

Figure 77. Map of Sites Where Lateral Wander of Trucks Was Measured in Arizona.

111

Figure 78. Histogram and Fitted Normal Distribution Curve Showing
the Distribution of Wheel Lateral Wander.

112

The results of the analysis showed that the mean and standard deviation were as follows:
Analysis: Mean lateral distribution and standard deviation were computed for Arizona
sites:
o Mean lateral offset: 15 inches.
o Standard deviation: 12 inches.
Recommendations: Use these values for pavement design. If the lane is narrower, reduce
these values for design.
Impact: Lateral wander has a significant effect on transverse cracking in concrete
pavement and rutting in asphalt pavement.
These mean and standard deviation values are recommended for Arizona use, as they represent a
refinement of the national calibration values and may show a significant difference in design.
TRUCK WHEELBASE
The truck wheelbase was previously defined as the distance from the steering axle to the first
next axle for Classes 8 through 13 only. This distance varies from “short” to “medium” to “long”
truck cabs.
WIM data were downloaded from two Arizona LTPP sites. The data were divided into three
sections so that the average wheelbase for these three sections was 12, 15, and 18 feet. All trucks
in Classes 8 through 13 were evaluated. The percentage of trucks for each average wheelbase
section was determined (see Table 49).
Table 49. Wheelbase Distribution.
Wheelbase Type
Short
Medium
Long

Wheelbase Length (feet)
10.0 to 13.4
13.5 to 16.5
16.6 to 20.0

Percent of Trucks
(Class 8 through 13)
11
17
72

Results of the analysis showed that the mean and standard deviation were as follows:
Analysis: Data were analyzed and the following results obtained:
o Short wheelbase: 11 percent.
o Medium wheelbase: 17 percent.
o Long wheelbase: 72 percent.
Recommendations:
o Level 1: Use WIM data to compute the percentage of trucks in Classes 8 through
13 that have short, medium, and long wheelbases.
o Level 2/3: Use the results above.

113

114

CHAPTER 7. DETAILED SYSTEM FOR ADOT TRAFFIC DATA INPUTS
FOR THE MEPDG DESIGN PROCESS
This chapter provides detailed inputs for the ADOT comprehensive traffic data input system for
the MEPDG. This system recommends the following components:
A homogeneous traffic segment database that includes all highways in Arizona (Interstate,
U.S., and state). This database would include all traffic inputs required for the MEPDG
and AASHTO 1993 design procedures. Traffic segments would include MP to MP limits,
as well as GPS coordinates of the beginning and ending MP.
Coordinates, traffic volume inputs, traffic weight inputs, traffic geometry inputs, and
other inputs.
This chapter also discusses types of equipment recommended for collecting the traffic data,
based on the accuracies needed in support of the MEPDG. A cost estimate is provided for the
equipment, installation, site maintenance, equipment calibration, monitoring (data retrieval), and
data analyses.
OVERALL SUMMARY OF ARIZONA TRAFFIC DATA INPUT SYSTEM
The traffic data input system includes field data collection equipment, procedures to process the
raw data, a traffic segment database, and detailed procedures for obtaining the data required. The
traffic segment database would include the section breakdown currently included in the
pavement management system database used by pavement management and design groups. For
each segment of highway, all inputs for the MEPDG would be provided. Recommendations for
inputs for the initial version of the traffic segment database are provided in this chapter. The
general traffic segment database is presented using the format shown in Table 50.
DETAILED DESCRIPTION OF TRAFFIC SEGMENT DATABASE
The development of a traffic segment database was recommended in SPR-402 Project No. 11,
“Development of Design Guide Traffic Files for ADOT.” (Witczak, 2008) That study
recommended four major components of traffic information to be included in each section of the
database:
AADT.
Traffic growth rate.
Percent of trucks.
Vehicle classification percentage.

115

Table 50. ADOT Comprehensive Traffic Data Input System for the MEPDG.
MEPDG
Traffic
Input

Input
Level

Who Collects
and Processes
Input

How Is Input
Obtained?

How Often Is Input
Provided?

AVC for specific
As requested for
project
specific project
2
MPD
AVC
Annually
3
MPD
AVC
Annually
WIM for specific
As requested for
1
MPD
project
specific project
Weight
Inputs
WIM: urban, rural,
2/3
MPD
Annually
desert
Measured for
As requested for
1
PD
Geometry
specific project
specific project
Inputs
2/3
PD
AZ Default
Constant or annually
Measured for
As requested for
1
MPD
Other
specific project
specific project
Inputs
2/3
MPD
AZ Default
Constant or Annually
MPD = ADOT Multimodal Planning Division; PD = Pavement Design; PM = Pavement Manager.
Volume
Inputs

1

MPD

User of
Input
PD, PM
PD, PM
PD, PM
PD
PD
PD
PD
PD
PD

The traffic segment database would also include location inputs such as beginning and ending
MP and GPS coordinates of these locations. The MEPDG requires additional inputs that should
be stored in the database, including axle weight distribution data, truck lane percentage,
directional distribution of trucks, hourly distribution of trucks, and monthly truck volume
adjustments.
This database would provide a significant amount of information to pavement designers,
pavement management staff, and several others in ADOT, as well as consultants who design
projects for ADOT.
This database would be updated annually, with the results from the previous year of the traffic
data collection. Over time, it would become an excellent source of current and historical traffic
data. The database would be managed and updated by the MPD for use by the pavement design
and pavement management sections.
ADOT MEPDG Traffic Volume Inputs
The traffic segment database would provide all traffic volume inputs required for the MEPDG
along every state highway in Arizona. The traffic volume inputs are shown in Table 51, with all
recommendations provided for Levels 1, 2, and 3. Some further explanations are provided to
more fully describe the recommendations. Table 51 also shows the specific traffic inputs
required under this topic.

116

Table 51. Traffic Volume Inputs Required for the MEPDG.
How Is Input
Obtained?

How Often Is Input
Provided?

1
2/3

Who
Collects and
Processes
Input?
MPD
MPD

AVC for project
AVC

PD
PD, PM

Growth AADT

1
2/3

MPD
MPD

AVC for project
AVC

Vehicle Class
Distribution

1
2

MPD
MPD

AVC for project
AVC

Percent Trucks

3
1
2

SPR-672
MPD
MPD

Historical AVC
AVC for project
AVC

3
1
2/3

SPR-672
MPD
SPR-672

Historical AVC
AVC for project
Historical AVC

Directional
Distribution
Hourly AADTT

1
2/3
1
2/3

MPD
SPR-672
MPD
SPR-672

Monthly
Distribution

1
2/3

MPD
SPR-672

AVC for project
Historical AVC
AVC for project
Historical AVC
by highway class
or urban/rural?
AVC for project
Historical AVC
by highway class
or urban/rural?

As requested for project
Annual tables, maps,
pavement management
system software
As requested for project
Annual tables and
pavement management
system software
As requested for project
Annual tables and
pavement management
system software
Tables and guidelines
As requested for project
Annual tables and
pavement management
system software
Tables and guidelines
As requested for project
Guideline based on
number of lanes
As requested for project
Set to 0.50
As requested for project
Annual update

As requested for project
Set to 1.00, except for
exceptions (recreational,
industrial)

PD

MEPDG Traffic
Input
Initial AADT

Truck Lane
Distribution

Input
Level

User of Input

PD, PM
PD, PM

PD
PD, PM

PD
PD
PD, PM

PD
PD
PD
PD
PD, PM
PD
PD

Initial Two-Way AADT
The initial two-way AADT is a significant input because any error in this value will project itself
throughout the future design life of the pavement. When the initial AADT is multiplied by the
percentage of buses and trucks (Classes 4 through 13), the expected number of buses and trucks
(AADTT) in the base year is obtained. This is calculated from the AVC/WIM data or trip
generation studies by averaging the number of trucks measured over multiple 24-hour periods of
time in each season/month, and weighted between weekends and weekdays. The MPD collects
this input through remote download of raw data files from each traffic data collection device.
The data are then automatically processed and reduced using TRADAS software. AADTs for
each equipment site are calculated and presented in the software. The software then validates the
data through historical and multiple count AADT checks. The AADT is then assigned along each
highway to the various homogenous segments.
The AADT values collected and developed annually are made available to ADOT’s pavement
design and pavement management system sections through the ADOT Web site. Spreadsheets

117

are populated annually with these data, which are entered into the Basic pavement management
system software used by pavement design and management groups.
For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: Temporary AVC equipment is installed on the project site and data are
measured as described above over an appropriate sampling time. The data are then
processed and used as described above.
Level 2/3: AADT data are obtained from the annually updated and developed
spreadsheets for the project segment under design and projected to the initial year AADT.
Growth of AADTT (Truck Traffic)
Traditionally, ADOT has determined future truck traffic growth through a projection of historical
AADT (all vehicles). This implies that future growth will be as significant as past growth, which
may or may not be correct for various highway segments. It also assumes that truck volume
growth will be the same as all vehicle growth. The proper input is truck traffic growth (Classes 4
through 13).
The MEPDG allows the user to specify the nature and rate of traffic growth relative to the base
year. The MEPDG software (now called Pavement ME Design) can consider the growth for each
truck class separately. The user can choose one of three growth functions:
No growth: Truck volume remains the same throughout the design life.
Linear growth: The truck volume increases by a constant percentage of the base year
traffic across each truck class.
Compound growth: The truck volume increases by the constant percentage of the
preceding year’s traffic across each truck class.
The user can select a different growth rate and growth function for each truck class by selecting
the option for “vehicle-class specific traffic growth.”
For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: Determine the historic growth in AADTT by plotting AADTT over time for as
many years as available. Five or more years’ worth of data is desirable to reduce
unrealistically high or low values. These data will likely reflect a downturn in AADTT
due to the recession from 2007 to 2010. Then adjust this value up or down based on the
relative expected growth in the area of the highway. The recommended range is from 0 to
10 percent per year. If the resulting value is negative growth, use +2 percent.
Level 2/3: If no historical data are available for a highway segment, obtain data from
another segment as close or as representative as possible to the highway segment under
design. If no such data are available, use a value of +3 percent compound growth, which
is typical of major highways in Arizona.

118

Percent Trucks (T Factor)
Percent trucks is the percentage of the AADT volume generated by buses and trucks (percentage
of all vehicles identified as Classes 4 to 13 from the entire two-way truck count). The T factor is
the percentage of trucks to be used in the MEPDG design input and is multiplied by AADT to
obtain the direct MEPDG input AADTT. The truck percentage should be selected from the
existing ADOT spreadsheet, which is updated annually from data provided by the MPD. Since it
was determined that the values that currently populate this spreadsheet are valid, this practice
should continue.
For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: The percent of trucks is determined from AVC equipment located on or near the
project under design.
Level 2/3: The percent of trucks is are determined from the ADOT spreadsheet, which is
updated annually from data provided by the MPD.
Vehicle Class Distribution
The VCD for a given highway represents the percent of each type of vehicle (Classes 4
through 13). This input is important because it is used to compute the number of single, tandem,
tridem, and quad axles that pass on a highway over a design period. This input can be obtained
on site and from results of Arizona vehicle counts.
For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: Measure the VCD on the highway section under design through placement of
13-bin AVC equipment in the design lane or in all lanes. This measurement must be in
place for a minimum of 7 days, 24 hours per day.
Level 2/3: The approximate percentage of VCDs is developed from Arizona AVC
measured data. Table 52 shows the recommended selection criteria for TTCs based on
highway functional class in Arizona. The Arizona TTC VCD percentages calculated for
these TTCs are shown in Table 53.

119

Table 52. Recommended Selection Criteria for Level 3 Arizona TTCs Based on Highway
Functional Class.

Rural Principal Arterial – Interstate

AZ MEPDG
TTCs
1, 2

Rural Principal Arterial – Other

6, 9, 12

Rural Major Collector
Rural Minor Arterial or Collector

6, 9, 12
6, 9, 12, 14

Urban Principal Arterial – Interstate

1, 2

Urban Principal Arterial – Other

9, 12, 14

Functional Class

AZ Representative Highways
I-8, I-10, I-15, I-19, I-40 (single peak for Class 9)
SR 85, U.S. 60, SR 77, U.S. 93, SR 360, SR 101, SR 303
(double peak for Classes 5 and 9)
U.S. 91 (double peak for Classes 5 and 9)
SR 79, U.S. 60, SR 347 (double peak for Classes 5 and 9)
I-10, I-19, I-40 (some in urban areas had double peak
Classes 5 and 9)
SR 360, SR 101, SR 101, SR 303, SR 77 (double peak for
Classes 5 and 9)

Table 53. Recommended Level 3 VCDs for Specific Arizona TTCs.
AZ
TTC
1
2
6
9
12
14

4
1.8
3.1
3.7
5.3
5.3
7.8

5
6.5
14.7
21.3
38.5
46.3
65.8

6
1.9
2.9
5.7
6.2
5.7
4.4

7
0.2
0.1
0.4
0.2
0.7
0.2

Vehicle Class
8
9
10.3
73.2
9.3
64.4
19.0
45.6
9.0
36.9
16.1
24.1
11.7
9.1

10
1.0
1.3
1.7
1.8
1.1
0.7

11
3.1
1.9
1.5
1.3
0.3
0.2

12
1.9
1.5
0.7
0.3
0.1
0.0

13
0.1
0.8
0.4
0.4
0.3
0.1

Percent Trucks in the Design Lane
The percentage of trucks in the design lane is the percentage of total trucks in one direction
expected to use the design lane. If 100 trucks were using a highway with two lanes in one
direction and 85 were in the outer driving lane and 15 were in the inner passing lane, the percent
of trucks in the design lane would be 85 percent (outer lane). The percentage of trucks in the
design lane is used to calculate the total number of trucks and then axles expected to travel in the
design lane over the analysis period. A summary of data obtained for Arizona sections is shown
in Table 50.
For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: Install AVC equipment across all lanes in one direction and measure the number
of trucks each hour over at least a 7-day, 24-hour per day count. If the highway is to be
widened, the percentage of trucks in the design lane will likely be lower. Follow
recommendations provided for Level 2/3 to make an adjustment. Level 1 is
recommended specifically for unusual urban conditions where various ramp on/off
situations exist along the project. The critical area along the project (highest percentage
of trucks in one lane) should be used for the design.

120

Level 2/3: Use the following statewide averages for truck lane distribution design (see
Table 54):
o One lane in design direction: 100 percent.
o Two lanes in design direction: 81 percent (60 to 97 measured).
o Three lanes in design direction: 51 percent (40 to 62 measured).
o Four or more lanes in design direction: 44 percent (44 percent measured).
Table 54. Percent of Trucks in Design Lane for Arizona Sections.

Site

Route

Total No.
of Lanes
in Design
Direction

100767

SR 72

1

La Paz

SR 72

Rural Major Collector

100

East

100767

SR 72

1

La Paz

SR 72

Rural Major Collector

100

West

100854

SR 79

1

Pinal

SR 79

Rural Minor Arterial

100

North

100854

SR 79

1

Pinal

SR 79

100

South

101113

SR 95

1

Yuma

SR 95

100

North

101113

SR 95

1

Yuma

SR 95

100

South

101602

SR 303

1

Maricopa

SR 303

100

North

101602

SR 303

1

Maricopa

SR 303

100

South

101928

U.S. 60

1

Navajo

U.S. 60

Rural Minor Arterial
Rural Principal
Arterial - Other
Rural Principal
Arterial - Other
Urban Principal
Arterial - Other
Freeways or
Expressways
Urban Principal
Arterial - Other
Freeways or
Expressways
Rural Minor Arterial

100

East

101928

U.S. 60

1

Navajo

U.S. 60

100

West

102094

U.S. 93

1

Yavapai

U.S. 93

100

North

102094

U.S. 93

1

Yavapai

U.S. 93

Rural Minor Arterial
Rural Principal
Arterial - Other
Rural Principal
Arterial - Other

100

South

1

Graham

Rural Major Collector

100

North

1

Graham

Rural Major Collector

100

South

90

East

92

West

71

East

85

West

91

East

90

West

102230
102230

U.S.
191
U.S.
191

Arizona
County

Route
No.

U.S.
191
U.S.
191

100010

I-08

2

Yuma

I-08

100010

I-08

2

Yuma

I-08

100070

U.S. 60

2

La Paz

U.S. 60

100070

U.S. 60

2

La Paz

U.S. 60

100188

I-10

2

Cochise

I-10

100188

I-10

2

Cochise

I-10

121

Functional Class

Percent
Truck in
Design
Lane

Lane
Description

Rural Principal
Arterial - Interstate
Rural Principal
Arterial - Interstate
Rural Principal
Arterial - Interstate
Rural Principal
Arterial - Interstate
Rural Principal
Arterial - Interstate
Rural Principal
Arterial - Interstate

Table 54. Percent of Trucks in Design Lane for Arizona Sections, continued.

Site

Route

Lanes in
Design
Direction

100327

I-15

2

Mohave

I-15

100327

I-15

2

Mohave

I-15

100473

I-19

2

Pima

I-19

100473

I-19

2

Pima

I-19

100537

I-40

2

Coconino

I-40

100537

I-40

2

Coconino

I-40

100541

I-40

2

Coconino

I-40

100541

I-40

2

Coconino

I-40

100922

SR 85

2

Maricopa

100922

SR 85

2

Maricopa

2

Pinal

2

Pinal

2

Maricopa

2

Maricopa

2

Coconino

2

Coconino

2

Mohave

2

Mohave

101622
101622
101849
101849
102068
102068
102084
102084

SR
347
SR
347
U.S.
60
U.S.
60
U.S.
89
U.S.
89
U.S.
93
U.S.
93

Arizona
County

Rout
e No.

SR
85
SR
85
SR
347
SR
347
U.S.
60
U.S.
60
U.S.
89
U.S.
89
U.S.
93
U.S.
93

100139

I-10

3

Pima

I-10

100139

I-10

3

Pima

I-10

100800

SR 77

3

Pima

100800

SR 77

3

Pima

101248

SR
101

5

Maricopa

SR
101

101248

SR
101

5

Maricopa

SR
101

SR
77
SR
77

122

Percent
Truck in
Design
Lane

Lane
Description

88

North

89

South

63

North

65

South

85

East

88

West

80

East

83

West

93

North

93

South

Rural Minor Collector

73

North

Rural Minor Collector

75

South

79

East

60

West

75

North

67

South

97

North

78

South

56

East

62

West

47

North

40

South

44

North

44

South

Functional Class
Rural Principal
Arterial - Interstate
Rural Principal
Arterial - Interstate
Urban Principal
Arterial - Interstate
Urban Principal
Arterial - Interstate
Rural Principal
Arterial - Interstate
Rural Principal
Arterial - Interstate
Urban Principal
Arterial - Interstate
Urban Principal
Arterial - Interstate
Rural Principal
Arterial - Other
Rural Principal
Arterial - Other

Rural Principal
Arterial - Other
Rural Principal
Arterial - Other
Urban Principal
Arterial - Other
Urban Principal
Arterial - Other
Rural Principal
Arterial - Other
Rural Principal
Arterial - Other
Urban Principal
Arterial - Interstate
Urban Principal
Arterial - Interstate
Urban Principal
Arterial - Other
Urban Principal
Arterial - Other
Urban Principal
Arterial - Other
Freeways or
Expressways
Urban Principal
Arterial - Other
Freeways or
Expressways

Percent Trucks in Design Direction
The percentage of trucks in the design direction is the percentage of trucks (from the entire twoway truck count) that is expected to travel in the design direction. Although this value should be
very close to 50 percent, it is not necessarily so, especially in cases where truck traffic does not
use the same route for both out and return trips.
For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: Install AVC equipment across all lanes in both directions and compute the
percentage of trucks in the design direction over a sufficient sample period on or near the
project under design.
Level 2: The Arizona statewide average is 50 percent (ranged from 36 to 64 percent).
This is approximately the MEPDG Level 3 default and should be used for Arizona
pavement designs.
Truck Hourly Distribution
Truck volume varies hour-to-hour over a 24-hour day. The following recommendations are
provided for 24-hour truck distribution:
Level 1: Measure the number of trucks (Classes 4 through 13) in the design lane each
hour over a representative number of 24-hour periods. It is recommended that a 7-day,
24-hour per day minimum count be conducted. The number of trucks in each hour is
divided by the total number of trucks counted over 24 hours to obtain a percentage for
every hour of the day and night.
Level 2/3: Three distinct hourly truck distributions are recommended for Arizona—rural,
urban, and long-haul desert. These distributions are described as follows:
o Moderate Peak for Rural Highways: A distribution that represents “rural”
highway trucks over 24 hours. The difference between the nighttime and daytime
truck traffic is significant (typically ranges from 3 to 7 percent), but not as peaked
as typical urban distribution. An example of this “rural” hourly truck distribution
is shown in Figure 79, which is for a site in Coconino County on I-40.
o High Peak Distribution for Urban Highways: A distribution that represents
“urban” highway trucks over 24 hours. The difference between the daytime and
nighttime truck traffic is typically higher than for rural sites. The difference
between nighttime and daytime truck traffic typically ranges from less than 1
percent at nighttime to greater than 9 percent at daytime. An example of an
“urban” hourly truck distribution is shown in Figure 80, which is for site
4_100800 located in urban Pima County on SR 77.
o Desert Long-Haul Highways (Flat Distribution): A distribution that represents
a long-haul section of rural highway across the desert. This distribution is far
flatter than either the rural or urban distributions. An example is section 100070
on the western end of I-10 in La Paz County, shown in Figure 81.

123

These three, 24-hour truck distributions, recommended for use in design for Level 2/3 input to
the MEPDG, are provided in Table 55.
SectionID=4_100537

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure 79. Typical Arizona Rural 24-Hour Distribution of Trucks.
SectionID=4_100800

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure 80. Typical Arizona 24-hour Urban Distribution of Trucks.

124

SectionID=4_100070

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure 81. Typical 24-Hour Long-Haul Distance Desert Distribution of Trucks.
Table 55. Summary of 24-Hour Truck Distributions Recommended for Arizona MEPDG
for Input Level 2/3 by Rural and Urban Functional Class.
Time of Day (24-hour
clock)
1 Early morning
2
3
4
5
6
7
8
9
10
11
12 Noon
13
14
15
16
17
18
19
20
21
22
23
24 Midnight

“Rural” Distribution

“Urban” Distribution

1.9
1.7
1.6
1.7
1.8
2.3
3.2
4.1
5.0
5.8
6.3
6.6
6.8
6.7
6.6
6.3
5.9
5.4
4.8
4.1
3.6
3.2
2.6
2.2

0.9
0.8
0.7
1.0
2.0
3.6
5.5
6.1
6.6
7.0
7.1
7.0
6.8
6.8
6.8
6.3
5.8
5.0
4.1
3.2
2.5
2.0
1.5
1.1

125

“Long-Haul Desert”
Distribution
3.7
3.4
2.9
2.8
2.6
2.6
3.0
3.2
3.8
4.2
4.5
4.7
4.7
5.0
5.3
5.3
5.4
5.3
5.3
4.9
4.7
4.4
4.4
4.1

Monthly Truck Adjustment
The MAF input in the MEPDG provides the opportunity to fine-tune the design considering
month-to-month truck volumes. The national defaults were 1.00 for each month, which provides
for the same truck volume each month of a given year. The MAF was computed for a number of
sites in Arizona to determine its variation around the state. Results from the analysis showed that
the MAF factors for various highways over a 12-month period were very similar, with a few
exceptions.
For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: Measure the MAF using AVC equipment on or near the highway section under
design. A minimum of 7 days and 24 hours per day is required.
Level 2/3: Use the values determined for Arizona for all months unless there is some
known reason why truck traffic would vary significantly. For example, this could occur
on a highway in mountainous area used only by recreational vehicles in the summer
months. The MAF could then be varied to reflect this knowledge.
ADOT MEPDG Traffic Weight Inputs
Recommended sources for truck traffic axle weight inputs are shown in Table 56. Some further
explanations are provided to more fully describe the recommendations. Table 56 also shows the
specific traffic inputs required under this topic. A summary of recommended truck weight inputs
for Arizona MEPDG for input Level 2/3 is presented in Tables 57 through 68.
Table 56. Traffic Weight Inputs Required.
MEPDG Traffic
Input
Axle Load
Distributions:
Single,
Tandem,
Tridem, Quad

Input
Level

Who Collects
and Processes
Input

How Is Input
Obtained

How Often Is Input
Provided

User of
Input

1

MPD

Representative
WIM

2

MPD

AZ WIM mean

As requested for
project, normalized
Annually updated,
normalized tables

PD

SPR-672

AZ WIM mean by
highway class or
urban/rural

3

126

SPR-672 final report

Table 57. Summary of Level 2/3 Single Axle ALD Recommended for Arizona Rural
Principal Arterials, Interstate.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

10

11

12

13

3,000

0.038

0.486

0.000

0.973

4.537

0.210

0.310

0.460

0.271

1.896

4,000

0.050

4.309

0.002

0.325

7.207

0.443

0.102

1.552

1.152

1.431

5,000

0.050

10.099

0.374

0.604

4.568

0.610

0.107

2.697

2.160

1.439

6,000

0.561

24.219

2.839

1.130

12.103

1.374

0.952

4.161

4.024

2.560

7,000

1.186

12.469

3.379

1.569

8.580

1.938

1.709

5.079

6.453

3.890

8,000

2.753

8.969

3.971

2.240

7.778

2.871

3.149

6.035

7.945

4.738

9,000

5.038

7.621

6.495

4.258

8.637

5.029

6.124

7.079

8.436

6.337

10,000

7.637

6.402

10.604

1.845

9.136

9.190

11.881

8.643

9.645

7.880

11,000

9.989

5.215

14.328

9.324

8.390

14.862

17.107

9.816

10.853

10.451

12,000

13.469

4.577

16.163

9.040

7.190

19.357

19.704

9.964

11.722

12.204

13,000

14.165

3.573

13.318

5.189

5.256

17.404

15.820

8.913

10.620

11.182

14,000

12.605

2.770

8.826

10.954

3.797

10.360

9.559

7.502

8.067

8.574

15,000

9.455

2.186

6.182

9.957

2.941

5.397

5.321

6.415

6.276

5.654

16,000

6.763

1.714

4.304

6.482

2.287

3.385

3.034

5.554

4.598

4.316

17,000

4.416

1.347

3.049

7.679

1.877

2.393

1.907

4.641

3.063

3.721

18,000

3.101

1.067

1.991

6.646

1.467

1.745

1.319

3.730

1.884

2.777

19,000

2.432

0.804

1.323

4.462

1.119

1.240

0.695

2.730

1.201

2.466

20,000

1.873

0.601

0.878

3.590

0.816

0.824

0.407

1.917

0.667

2.301

21,000

1.367

0.446

0.650

2.700

0.551

0.514

0.233

1.250

0.362

1.282

22,000

0.944

0.311

0.396

1.885

0.374

0.307

0.122

0.744

0.244

1.167

23,000

0.661

0.207

0.281

2.898

0.259

0.171

0.097

0.462

0.140

0.747

24,000

0.513

0.146

0.205

1.663

0.164

0.099

0.048

0.248

0.095

0.626

25,000

0.296

0.094

0.114

1.586

0.105

0.064

0.038

0.139

0.039

0.521

26,000

0.219

0.064

0.089

1.231

0.059

0.039

0.031

0.079

0.017

0.367

27,000

0.131

0.037

0.056

0.732

0.043

0.026

0.044

0.055

0.016

0.299

28,000

0.118

0.029

0.044

0.280

0.028

0.018

0.026

0.035

0.011

0.166

29,000

0.055

0.026

0.033

0.050

0.020

0.007

0.007

0.020

0.006

0.177

30,000

0.045

0.013

0.014

0.112

0.012

0.003

0.031

0.009

0.000

0.145

31,000

0.015

0.006

0.018

0.125

0.005

0.004

0.005

0.004

0.001

0.063

32,000

0.016

0.007

0.011

0.000

0.003

0.003

0.005

0.005

0.000

0.032

33,000

0.006

0.006

0.005

0.000

0.002

0.002

0.002

0.003

0.000

0.038

34,000

0.004

0.003

0.003

0.308

0.002

0.006

0.007

0.002

0.001

0.032

35,000

0.002

0.004

0.005

0.000

0.001

0.001

0.006

0.002

0.000

0.032

36,000

0.001

0.003

0.001

0.029

0.002

0.001

0.018

0.003

0.000

0.018

37,000

0.009

0.004

0.004

0.000

0.003

0.000

0.004

0.002

0.000

0.023

38,000

0.001

0.002

0.003

0.057

0.001

0.001

0.005

0.000

0.001

0.028

39,000

0.004

0.002

0.004

0.048

0.000

0.001

0.003

0.002

0.000

0.004

40,000

0.004

0.002

0.004

0.019

0.001

0.001

0.000

0.000

0.000

0.007

41,000

0.010

0.002

0.011

0.000

0.002

0.014

0.030

0.000

0.000

0.065

127

Table 58. Summary of Level 2/3 Tandem Axle ALD Recommended for Arizona Rural
Principal Arterials, Interstate.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

10

11

12

13

6,000

0.011

0.000

0.290

0.000

5.050

0.141

0.188

0.000

0.111

0.714

8,000

0.011

0.000

4.419

0.000

7.927

0.747

0.636

50.000

0.563

1.083

10,000

0.018

0.000

10.371

0.000

5.991

1.799

1.565

25.000

2.054

2.590

12,000

0.090

0.000

14.419

0.000

8.533

3.519

2.762

0.000

4.427

5.103

14,000

0.301

0.000

13.063

0.000

11.528

5.235

5.318

0.000

8.715

6.632

16,000

0.807

0.000

8.055

0.000

12.541

6.013

6.893

0.000

12.451

6.310

18,000

2.583

0.000

5.543

100.00

11.386

6.240

8.209

0.000

13.291

6.604

20,000

5.417

0.000

4.607

0.000

9.107

6.284

7.922

0.000

14.918

5.181

22,000

9.568

0.000

4.618

0.000

6.941

6.165

8.416

0.000

14.368

5.148

24,000

13.467

0.000

5.081

0.000

5.326

6.388

8.015

0.000

12.356

4.560

26,000

15.595

0.000

5.359

0.000

3.988

6.667

7.735

0.000

8.337

4.293

28,000

15.288

0.000

5.137

0.000

2.989

7.087

7.740

0.000

4.441

4.377

30,000

12.411

0.000

4.544

0.000

2.190

7.796

7.462

0.000

1.967

4.153

32,000

9.015

0.000

3.866

0.000

1.772

8.362

6.391

0.000

1.000

4.583

34,000

6.407

0.000

2.885

0.000

1.256

8.232

5.366

0.000

0.377

5.106

36,000

3.582

0.000

2.296

0.000

0.956

7.160

4.827

25.000

0.182

5.626

38,000

1.935

0.000

1.705

0.000

0.777

5.210

3.127

0.000

0.137

5.551

40,000

1.306

0.000

1.188

0.000

0.501

3.086

2.436

0.000

0.068

4.950

42,000

0.738

0.000

0.866

0.000

0.303

1.683

1.647

0.000

0.036

4.187

44,000

0.503

0.000

0.552

0.000

0.218

0.895

1.096

0.000

0.019

3.269

46,000

0.377

0.000

0.435

0.000

0.098

0.514

0.774

0.000

0.006

2.382

48,000

0.212

0.000

0.244

0.000

0.170

0.302

0.432

0.000

0.011

1.809

50,000

0.138

0.000

0.140

0.000

0.037

0.174

0.326

0.000

0.030

1.453

52,000

0.065

0.000

0.102

0.000

0.020

0.101

0.164

0.000

0.000

1.050

54,000

0.045

0.000

0.053

0.000

0.009

0.059

0.172

0.000

0.000

0.820

56,000

0.027

0.000

0.035

0.000

0.006

0.034

0.116

0.000

0.000

0.627

58,000

0.022

0.000

0.024

0.000

0.011

0.016

0.060

0.000

0.010

0.514

60,000

0.010

0.000

0.019

0.000

0.004

0.006

0.036

0.000

0.005

0.305

62,000

0.007

0.000

0.014

0.000

0.003

0.004

0.026

0.000

0.000

0.269

64,000

0.011

0.000

0.009

0.000

0.001

0.002

0.065

0.000

0.095

0.194

66,000

0.001

0.000

0.004

0.000

0.001

0.001

0.018

0.000

0.000

0.122

68,000

0.003

0.000

0.005

0.000

0.001

0.001

0.015

0.000

0.000

0.106

70,000

0.003

0.000

0.003

0.000

0.001

0.000

0.011

0.000

0.000

0.111

72,000

0.001

0.000

0.002

0.000

0.000

0.000

0.001

0.000

0.000

0.062

74,000

0.000

0.000

0.007

0.000

0.000

0.000

0.002

0.000

0.000

0.076

76,000

0.000

0.000

0.002

0.000

0.000

0.000

0.001

0.000

0.000

0.039

78,000

0.000

0.000

0.001

0.000

0.000

0.000

0.001

0.000

0.000

0.024

80,000

0.000

0.000

0.002

0.000

0.000

0.000

0.004

0.000

0.000

0.010

82,000

0.000

0.000

0.000

0.000

0.000

0.000

0.005

0.000

0.000

0.003

128

Table 59. Summary of Level 2/3 Tridem Axle ALD Recommended for Arizona Rural
Principal Arterials, Interstate.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

12,000

0.000

0.000

0.000

0.407

0.000

15,000

0.000

0.000

0.000

0.394

18,000

0.000

0.000

0.000

5.444

21,000

0.000

0.000

0.000

24,000

0.000

0.000

0.000

27,000

0.000

0.000

30,000

0.000

0.000

33,000

0.000

36,000

0.000

39,000

10

11

12

13

0.105

0.735

0.000

3.111

0.594

0.000

1.295

2.336

0.000

3.842

1.000

0.000

33.438

6.388

0.000

7.616

1.431

5.957

0.000

12.495

9.254

0.000

9.580

2.955

5.374

0.000

9.010

9.670

0.000

20.038

3.998

0.000

3.184

0.000

5.533

8.246

0.000

13.931

4.515

0.000

3.707

0.000

1.862

6.863

0.000

16.044

5.753

0.000

0.000

3.412

0.000

1.067

7.361

0.000

1.338

3.861

0.000

0.000

6.737

0.000

1.571

7.440

0.000

1.418

4.878

0.000

0.000

0.000

6.619

0.000

1.510

7.897

0.000

8.847

6.155

42,000

0.000

0.000

0.000

11.794

0.000

1.286

8.187

0.000

0.236

6.803

45,000

0.000

0.000

0.000

9.811

0.000

0.410

7.334

0.000

0.342

6.066

48,000

0.000

0.000

0.000

11.127

0.000

0.614

5.520

0.000

1.453

6.879

51,000

0.000

0.000

0.000

7.935

0.000

4.971

3.890

0.000

3.549

7.441

54,000

0.000

0.000

0.000

5.380

0.000

2.495

2.809

0.000

1.596

11.680

57,000

0.000

0.000

0.000

3.377

0.000

5.429

2.036

0.000

2.471

5.717

60,000

0.000

0.000

0.000

3.084

0.000

4.762

1.670

0.000

1.111

6.126

63,000

0.000

0.000

0.000

3.335

0.000

2.381

0.817

0.000

2.458

4.731

66,000

0.000

0.000

0.000

2.002

0.000

0.000

0.552

0.000

0.000

3.632

69,000

0.000

0.000

0.000

0.483

0.000

9.524

0.395

0.000

0.513

2.345

72,000

0.000

0.000

0.000

0.121

0.000

0.000

0.250

0.000

0.000

0.801

75,000

0.000

0.000

0.000

0.300

0.000

0.000

0.126

0.000

0.000

0.972

78,000

0.000

0.000

0.000

0.000

0.000

0.000

0.074

0.000

0.000

1.026

81,000

0.000

0.000

0.000

0.000

0.000

0.000

0.055

0.000

0.000

0.211

84,000

0.000

0.000

0.000

0.000

0.000

0.000

0.026

0.000

0.000

0.218

87,000

0.000

0.000

0.000

0.000

0.000

0.000

0.021

0.000

0.000

0.016

90,000

0.000

0.000

0.000

0.000

0.000

0.000

0.009

0.000

0.000

0.037

93,000

0.000

0.000

0.000

0.000

0.000

0.000

0.004

0.000

0.513

0.017

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.002

0.000

0.000

0.011

99,000

0.000

0.000

0.000

0.000

0.000

0.000

0.001

0.000

0.000

0.005

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.001

0.000

0.000

0.000

129

Table 60. Summary of Level 2/3 Quad Axle ALD Recommended for Arizona Rural
Principal Arterials, Interstate.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

10

11

12

13

12,000

0.000

0.000

0.000

0.000

0.000

0.000

0.541

0.000

0.000

0.335

15,000

0.000

0.000

0.000

0.000

0.000

7.000

0.312

0.000

1.753

0.329

18,000

0.000

0.000

0.000

0.280

0.000

2.000

2.297

0.000

0.000

1.589

21,000

0.000

0.000

0.000

0.280

0.000

15.375

3.921

0.000

10.526

4.071

24,000

0.000

0.000

0.000

0.820

0.000

3.440

5.838

0.000

10.526

6.419

27,000

0.000

0.000

0.000

10.000

0.000

8.215

1.241

0.000

1.753

6.580

30,000

0.000

0.000

0.000

0.000

0.000

10.000

0.376

0.000

1.753

3.973

33,000

0.000

0.000

0.000

1.060

0.000

5.625

1.515

0.000

5.263

6.529

36,000

0.000

0.000

0.000

0.280

0.000

0.000

4.541

0.000

0.000

5.374

39,000

0.000

0.000

0.000

0.540

0.000

0.000

6.162

0.000

12.016

9.536

42,000

0.000

0.000

0.000

11.260

0.000

0.000

5.503

0.000

2.295

8.463

45,000

0.000

0.000

0.000

14.200

0.000

0.000

12.556

0.000

4.874

7.089

48,000

0.000

0.000

0.000

4.140

0.000

0.000

10.197

0.000

5.668

6.515

51,000

0.000

0.000

0.000

14.600

0.000

10.000

9.732

0.000

13.868

4.971

54,000

0.000

0.000

0.000

11.700

0.000

0.000

8.729

0.000

15.579

4.699

57,000

0.000

0.000

0.000

21.360

0.000

0.000

8.024

0.000

7.979

5.794

60,000

0.000

0.000

0.000

3.640

0.000

0.625

3.126

0.000

3.958

2.460

63,000

0.000

0.000

0.000

3.520

0.000

10.000

3.159

0.000

1.363

2.749

66,000

0.000

0.000

0.000

1.840

0.000

0.000

2.935

0.000

0.532

1.945

69,000

0.000

0.000

0.000

0.540

0.000

0.000

3.038

0.000

0.000

1.293

72,000

0.000

0.000

0.000

0.000

0.000

0.000

0.544

0.000

0.274

1.304

75,000

0.000

0.000

0.000

0.000

0.000

0.000

0.450

0.000

0.000

1.224

78,000

0.000

0.000

0.000

0.000

0.000

0.000

2.382

0.000

0.000

1.979

81,000

0.000

0.000

0.000

0.000

0.000

15.000

0.000

0.000

0.000

1.696

84,000

0.000

0.000

0.000

0.000

0.000

0.000

0.121

0.000

0.000

1.705

87,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.234

90,000

0.000

0.000

0.000

0.000

0.000

7.500

0.782

0.000

0.000

0.406

93,000

0.000

0.000

0.000

0.000

0.000

0.000

1.471

0.000

0.000

0.061

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.036

99,000

0.000

0.000

0.000

0.000

0.000

2.500

0.000

0.000

0.000

0.001

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

130

Table 61. Summary of Level 2/3 Single Axle ALD Recommended for Arizona Urban
Freeways and Rural Minor Arterials/Collectors.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

10

11

12

13

3,000

0.000

0.483

0.003

0.000

1.870

0.327

0.110

1.197

0.547

2.010

4,000

0.003

5.240

0.007

0.130

4.660

1.167

0.203

4.313

2.613

1.910

5,000

0.000

6.467

0.013

0.377

3.513

1.820

0.347

6.103

4.260

1.053

6,000

0.813

24.707

1.520

0.343

9.947

2.287

1.103

6.173

5.973

1.743

7,000

2.597

12.997

2.213

1.303

8.213

2.587

2.640

6.763

8.160

2.820

8,000

5.853

9.477

3.910

1.437

9.240

4.280

5.057

7.827

9.503

4.083

9,000

9.740

7.770

7.057

2.677

10.167

8.300

9.987

8.813

11.223

7.913

10,000

10.473

6.267

10.717

4.523

9.520

12.957

13.567

8.070

10.720

11.610

11,000

10.533

5.100

12.917

10.240

8.227

15.793

16.677

6.693

9.950

12.047

12,000

10.333

4.387

13.483

5.933

7.130

16.363

17.030

5.870

9.523

11.620

13,000

8.970

3.577

11.367

7.757

5.573

12.140

11.493

5.030

7.123

9.320

14,000

7.987

2.790

8.947

9.630

4.357

7.240

8.203

4.840

5.310

7.103

15,000

6.293

2.270

7.070

8.387

3.700

4.337

4.417

4.787

4.083

4.960

16,000

5.657

1.857

5.527

6.800

3.067

2.937

3.197

4.830

2.797

4.430

17,000

4.760

1.473

4.087

8.147

2.543

2.107

1.650

4.370

2.287

3.303

18,000

3.880

1.240

3.173

6.060

2.010

1.587

0.997

3.840

1.537

2.713

19,000

3.613

0.940

2.177

5.787

1.557

1.143

0.993

2.983

1.280

2.183

20,000

2.513

0.757

1.810

4.810

1.213

0.860

0.850

2.310

1.030

1.830

21,000

1.903

0.557

1.357

3.797

0.913

0.603

0.447

1.560

0.607

2.127

22,000

1.477

0.423

0.830

7.473

0.657

0.367

0.390

1.087

0.503

0.940

23,000

0.833

0.303

0.583

1.657

0.473

0.243

0.217

0.747

0.297

1.150

24,000

0.763

0.230

0.333

0.977

0.343

0.150

0.133

0.527

0.137

0.530

25,000

0.373

0.187

0.210

0.467

0.217

0.097

0.060

0.333

0.097

0.417

26,000

0.277

0.113

0.163

0.213

0.157

0.073

0.090

0.263

0.097

0.410

27,000

0.150

0.060

0.083

0.203

0.120

0.047

0.083

0.183

0.060

0.263

28,000

0.070

0.040

0.087

0.517

0.077

0.033

0.010

0.103

0.050

0.140

29,000

0.027

0.027

0.090

0.160

0.067

0.017

0.013

0.080

0.040

0.093

30,000

0.030

0.023

0.020

0.017

0.030

0.013

0.003

0.067

0.020

0.137

31,000

0.013

0.017

0.033

0.153

0.020

0.003

0.007

0.043

0.020

0.123

32,000

0.010

0.010

0.040

0.007

0.020

0.003

0.000

0.033

0.017

0.033

33,000

0.003

0.010

0.027

0.053

0.007

0.003

0.000

0.023

0.013

0.100

34,000

0.003

0.003

0.013

0.000

0.007

0.003

0.000

0.020

0.010

0.017

35,000

0.023

0.003

0.003

0.000

0.013

0.003

0.017

0.010

0.017

0.013

36,000

0.000

0.003

0.010

0.003

0.003

0.003

0.003

0.013

0.007

0.037

37,000

0.003

0.007

0.023

0.000

0.003

0.003

0.027

0.010

0.007

0.017

38,000

0.000

0.003

0.020

0.000

0.003

0.003

0.000

0.007

0.010

0.010

39,000

0.000

0.003

0.007

0.000

0.003

0.003

0.003

0.007

0.010

0.007

40,000

0.000

0.003

0.023

0.000

0.003

0.000

0.000

0.007

0.003

0.003

41,000

0.003

0.003

0.007

0.000

0.003

0.003

0.000

0.003

0.003

0.000

131

Table 62. Summary of Level 2/3 Tandem Axle ALD Recommended for Arizona Urban
Freeways and Rural Minor Arterials/Collectors.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

10

11

12

13

6,000

0.000

0.000

0.487

0.000

1.720

0.340

0.230

0.000

0.070

0.253

8,000

0.017

0.000

4.410

0.000

7.433

2.333

1.273

0.000

1.070

1.060

10,000

0.090

0.000

6.453

0.000

6.467

5.373

2.423

0.000

3.877

3.793

12,000

0.373

0.000

7.197

0.000

9.687

7.783

6.507

0.000

9.180

7.917

14,000

0.807

0.000

7.500

0.000

10.947

8.717

8.117

0.000

16.933

10.177

16,000

1.670

0.000

7.300

0.000

10.387

8.217

9.567

0.000

17.207

8.763

18,000

3.877

0.000

6.697

0.000

8.320

7.120

9.403

0.000

15.760

6.820

20,000

10.083

0.000

6.373

0.000

7.063

6.110

8.683

0.000

11.910

4.950

22,000

11.833

0.000

6.150

0.000

5.307

5.460

7.567

0.000

6.963

3.857

24,000

14.067

0.000

6.410

0.000

4.727

5.593

6.893

0.000

6.037

4.053

26,000

14.563

0.000

6.407

0.000

4.270

5.863

5.847

0.000

4.307

4.277

28,000

11.913

0.000

6.173

0.000

3.900

6.240

5.907

0.000

2.640

4.203

30,000

9.687

0.000

5.530

0.000

3.847

6.450

4.920

0.000

1.177

4.330

32,000

6.043

0.000

4.713

0.000

3.463

6.103

4.453

0.000

0.970

4.870

34,000

4.753

0.000

3.990

0.000

2.957

5.213

4.053

0.000

0.517

4.533

36,000

3.437

0.000

3.450

0.000

2.517

4.003

2.590

0.000

0.343

3.907

38,000

2.640

0.000

2.653

0.000

1.957

2.857

2.283

0.000

0.337

3.527

40,000

1.833

0.000

2.250

0.000

1.353

1.967

2.227

0.000

0.130

3.023

42,000

0.940

0.000

1.793

0.000

0.980

1.323

1.940

0.000

0.120

2.593

44,000

0.527

0.000

1.103

0.000

0.787

0.907

1.417

0.000

0.067

2.447

46,000

0.273

0.000

0.810

0.000

0.587

0.610

1.073

0.000

0.063

1.883

48,000

0.247

0.000

0.707

0.000

0.347

0.410

0.717

0.000

0.050

1.550

50,000

0.133

0.000

0.413

0.000

0.253

0.290

0.447

0.000

0.043

1.553

52,000

0.080

0.000

0.287

0.000

0.143

0.183

0.473

0.000

0.077

1.013

54,000

0.080

0.000

0.223

0.000

0.097

0.123

0.327

0.000

0.023

1.100

56,000

0.037

0.000

0.133

0.000

0.057

0.077

0.227

0.000

0.023

0.713

58,000

0.013

0.000

0.093

0.000

0.033

0.060

0.110

0.000

0.027

0.713

60,000

0.003

0.000

0.073

0.000

0.013

0.040

0.143

0.000

0.030

0.437

62,000

0.003

0.000

0.040

0.000

0.017

0.023

0.077

0.000

0.017

0.493

64,000

0.003

0.000

0.030

0.000

0.017

0.020

0.063

0.000

0.020

0.320

66,000

0.000

0.000

0.027

0.000

0.013

0.017

0.020

0.000

0.017

0.257

68,000

0.000

0.000

0.003

0.000

0.003

0.013

0.010

0.000

0.013

0.163

70,000

0.000

0.000

0.013

0.000

0.007

0.010

0.007

0.000

0.003

0.107

72,000

0.000

0.000

0.013

0.000

0.000

0.007

0.003

0.000

0.000

0.107

74,000

0.000

0.000

0.017

0.000

0.000

0.007

0.000

0.000

0.000

0.083

76,000

0.000

0.000

0.000

0.000

0.000

0.007

0.000

0.000

0.000

0.043

78,000

0.000

0.000

0.000

0.000

0.000

0.003

0.000

0.000

0.000

0.020

80,000

0.000

0.000

0.003

0.000

0.000

0.000

0.000

0.000

0.000

0.023

82,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.003

0.010

132

Table 63. Summary of Level 2/3 Tridem Axle ALD Recommended for Arizona Urban
Freeways and Rural Minor Arterials/Collectors.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

12,000

0.000

0.000

0.000

0.000

0.000

15,000

0.000

0.000

0.000

0.017

0.000

18,000

0.000

0.000

0.000

4.223

0.000

21,000

0.000

0.000

0.000

0.313

0.000

24,000

0.000

0.000

0.000

2.490

0.000

27,000

0.000

0.000

0.000

3.347

30,000

0.000

0.000

0.000

1.907

33,000

0.000

0.000

0.000

36,000

0.000

0.000

0.000

39,000

0.000

0.000

42,000

0.000

45,000

0.000

48,000
51,000

10

11

12

13

1.187

0.000

0.000

0.177

0.000

4.453

0.000

7.288

2.030

66.667

13.067

0.000

14.169

3.180

0.000

9.680

0.000

14.750

4.303

0.044

7.483

0.000

19.200

3.123

0.000

0.133

7.557

0.000

10.631

3.933

0.000

1.167

5.907

0.000

0.000

1.653

3.587

0.000

2.456

7.013

0.000

8.506

3.487

7.653

0.000

1.533

6.147

0.000

0.675

2.563

0.000

7.900

0.000

1.589

5.463

0.000

3.300

3.720

0.000

0.000

10.507

0.000

3.222

6.010

0.000

1.550

5.807

0.000

0.000

11.580

0.000

2.678

5.750

0.000

0.694

6.150

0.000

0.000

0.000

18.143

0.000

1.856

4.740

0.000

2.938

9.500

0.000

0.000

0.000

7.083

0.000

4.867

4.057

0.000

4.469

7.980

54,000

0.000

0.000

0.000

6.513

0.000

12.056

2.977

0.000

0.694

6.273

57,000

0.000

0.000

0.000

4.247

0.000

1.511

2.370

0.000

10.775

4.353

60,000

0.000

0.000

0.000

6.077

0.000

0.089

1.907

0.000

0.175

7.800

63,000

0.000

0.000

0.000

2.560

0.000

0.044

1.407

0.000

0.175

2.747

66,000

0.000

0.000

0.000

0.727

0.000

0.011

0.860

0.000

0.000

6.403

69,000

0.000

0.000

0.000

0.347

0.000

0.022

0.690

0.000

0.000

3.793

72,000

0.000

0.000

0.000

0.487

0.000

0.022

0.360

0.000

0.000

2.597

75,000

0.000

0.000

0.000

0.050

0.000

0.011

0.260

0.000

0.000

1.513

78,000

0.000

0.000

0.000

0.090

0.000

0.000

0.337

0.000

0.000

0.807

81,000

0.000

0.000

0.000

0.007

0.000

0.000

0.113

0.000

0.000

1.097

84,000

0.000

0.000

0.000

0.120

0.000

0.000

0.077

0.000

0.000

0.230

87,000

0.000

0.000

0.000

0.007

0.000

0.000

0.057

0.000

0.000

0.257

90,000

0.000

0.000

0.000

0.013

0.000

0.000

0.013

0.000

0.000

0.140

93,000

0.000

0.000

0.000

0.000

0.000

0.000

0.040

0.000

0.000

0.440

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.020

0.000

0.000

0.000

99,000

0.000

0.000

0.000

0.003

0.000

0.000

0.007

0.000

0.000

3.793

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.050

133

0.000

Table 64. Summary of Level 2/3 Quad Axle ALD Recommended for Arizona Urban
Freeways and Rural Minor Arterials/Collectors.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

10

11

12

13

12,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.015

15,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.815

18,000

0.000

0.000

0.000

0.200

0.000

0.000

0.219

0.000

0.000

7.326

21,000

0.000

0.000

0.000

0.200

0.000

6.660

0.971

0.000

0.000

4.178

24,000

0.000

0.000

0.000

0.200

0.000

20.000

0.300

0.000

0.000

4.859

27,000

0.000

0.000

0.000

0.200

0.000

0.000

1.181

0.000

2.100

7.944

30,000

0.000

0.000

0.000

0.900

0.000

0.000

0.900

0.000

0.150

7.719

33,000

0.000

0.000

0.000

1.800

0.000

0.000

1.290

0.000

0.975

5.319

36,000

0.000

0.000

0.000

6.400

0.000

0.000

4.143

0.000

0.850

5.889

39,000

0.000

0.000

0.000

14.800

0.000

0.000

5.643

0.000

9.200

9.563

42,000

0.000

0.000

0.000

10.100

0.000

20.000

4.186

0.000

8.450

6.207

45,000

0.000

0.000

0.000

10.700

0.000

0.000

4.833

0.000

21.325

6.700

48,000

0.000

0.000

0.000

7.500

0.000

0.000

6.957

0.000

7.575

6.852

51,000

0.000

0.000

0.000

8.500

0.000

0.000

8.538

0.000

12.950

3.856

54,000

0.000

0.000

0.000

8.900

0.000

0.000

10.014

0.000

5.850

2.256

57,000

0.000

0.000

0.000

8.200

0.000

0.000

5.162

0.000

10.600

2.533

60,000

0.000

0.000

0.000

6.900

0.000

10.000

5.519

0.000

14.250

1.496

63,000

0.000

0.000

0.000

4.800

0.000

0.000

7.162

0.000

4.025

1.278

66,000

0.000

0.000

0.000

2.400

0.000

0.000

4.652

0.000

0.775

1.756

69,000

0.000

0.000

0.000

2.800

0.000

0.000

8.062

0.000

0.125

5.426

72,000

0.000

0.000

0.000

0.800

0.000

6.660

1.567

0.000

0.525

0.381

75,000

0.000

0.000

0.000

1.700

0.000

0.000

0.943

0.000

0.050

0.763

78,000

0.000

0.000

0.000

0.500

0.000

0.000

5.576

0.000

0.025

0.859

81,000

0.000

0.000

0.000

0.700

0.000

30.000

1.257

0.000

0.025

1.219

84,000

0.000

0.000

0.000

0.000

0.000

0.000

9.800

0.000

0.025

0.493

87,000

0.000

0.000

0.000

0.100

0.000

0.000

0.343

0.000

0.050

1.815

90,000

0.000

0.000

0.000

0.200

0.000

6.660

0.057

0.000

0.025

0.078

93,000

0.000

0.000

0.000

0.200

0.000

0.000

0.067

0.000

0.000

1.107

96,000

0.000

0.000

0.000

0.200

0.000

0.000

0.133

0.000

0.000

0.496

99,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.330

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.529

0.000

0.000

0.470

134

Table 65. Summary of Level 2/3 Single Axle ALD Recommended for Arizona Rural
Principal Arterials, Non-Interstate.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

10

11

12

13

3,000

0.003

0.883

0.000

0.268

7.963

0.403

0.215

0.458

0.173

0.348

4,000

0.000

6.158

0.000

3.246

12.843

0.993

0.053

0.993

0.468

0.765

5,000

0.005

33.240

0.420

0.251

9.020

1.703

0.118

2.935

1.208

1.635

6,000

0.078

25.343

3.210

1.284

11.650

2.588

0.370

2.500

3.103

3.095

7,000

0.235

8.685

5.378

3.576

8.488

1.403

0.540

5.060

9.008

12.428

8,000

1.083

5.198

2.755

5.981

6.773

1.435

0.825

4.350

7.508

14.968

9,000

1.465

4.983

2.673

2.530

6.020

2.550

1.690

5.795

7.558

5.345

10,000

2.310

4.010

4.870

5.332

5.710

5.595

5.570

8.723

7.918

5.715

11,000

4.288

3.025

11.203

4.830

5.978

9.620

16.163

11.168

11.265

14.053

12,000

7.043

2.248

16.895

8.141

5.313

21.498

27.958

8.678

15.065

14.655

13,000

12.550

1.538

16.353

14.792

4.295

24.273

25.995

5.653

11.558

8.393

14,000

21.823

1.143

14.953

16.403

3.025

7.993

10.668

5.115

6.730

4.933

15,000

25.410

0.890

9.360

3.327

2.118

2.548

3.368

5.235

6.960

2.445

16,000

14.423

0.660

4.123

2.741

1.685

2.190

2.438

6.020

4.200

3.035

17,000

5.383

0.513

2.115

12.332

1.370

3.025

1.868

6.408

3.088

1.503

18,000

1.698

0.453

2.020

3.022

1.228

4.368

0.598

6.413

1.653

1.535

19,000

0.710

0.340

1.573

1.519

1.065

3.920

0.308

5.008

1.188

1.785

20,000

0.495

0.225

0.935

2.976

0.925

2.398

0.008

5.458

0.665

0.873

21,000

0.338

0.170

0.430

1.751

0.658

0.960

0.000

2.548

0.528

0.638

22,000

0.195

0.105

0.333

3.341

0.403

0.328

0.000

0.830

0.045

0.218

23,000

0.155

0.063

0.153

0.043

0.208

0.078

1.278

0.288

0.020

0.188

24,000

0.145

0.028

0.023

0.132

0.128

0.005

0.000

0.183

0.000

0.153

25,000

0.083

0.013

0.020

0.000

0.018

0.005

0.000

0.028

0.000

0.068

26,000

0.033

0.005

0.050

0.314

0.013

0.003

0.000

0.010

0.005

0.038

27,000

0.020

0.000

0.033

0.014

0.003

0.000

0.000

0.030

0.005

0.088

28,000

0.005

0.000

0.000

0.000

0.003

0.000

0.000

0.010

0.000

0.033

29,000

0.003

0.000

0.025

0.000

0.003

0.000

0.000

0.003

0.000

0.000

30,000

0.000

0.000

0.020

0.000

0.003

0.000

0.000

0.010

0.000

0.000

31,000

0.000

0.000

0.008

0.000

0.000

0.000

0.000

0.003

0.000

0.000

32,000

0.003

0.000

0.000

0.000

0.003

0.000

0.000

0.003

0.000

0.000

33,000

0.008

0.000

0.008

0.000

0.000

0.000

0.000

0.003

0.000

0.005

34,000

0.003

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

35,000

0.000

0.000

0.003

0.924

0.000

0.000

0.000

0.003

0.000

0.000

36,000

0.008

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

37,000

0.000

0.000

0.015

0.000

0.000

0.000

0.000

0.000

0.000

0.000

38,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

39,000

0.000

0.000

0.000

0.700

0.000

0.000

0.000

0.000

0.000

0.000

40,000

0.000

0.000

0.008

0.000

0.000

0.000

0.000

0.000

0.000

0.020

41,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

135

Table 66. Summary of Level 2/3 Tandem Axle ALD Recommended for Arizona Rural
Principal Arterials, Non-Interstate.
Vehicle Class
9

Axle
Load, lb

4

5

6

7

8

10

11

12

13

6,000

0.000

0.000

0.013

0.000

14.135

0.078

0.168

0.000

0.000

0.165

8,000

0.000

0.000

0.275

0.000

7.453

0.525

0.220

0.000

0.015

0.795

10,000

0.023

0.000

3.400

0.000

2.855

2.173

0.415

0.000

0.108

2.188

12,000

0.035

0.000

12.353

0.000

4.743

3.555

0.808

0.000

0.368

15.225

14,000

0.073

0.000

7.678

0.000

9.233

4.945

2.640

0.000

9.020

19.918

16,000

0.173

0.000

7.775

0.000

12.365

5.000

5.895

0.000

8.268

12.485

18,000

0.468

0.000

6.498

0.000

10.983

4.555

8.575

0.000

12.258

5.343

20,000

0.450

0.000

4.740

0.000

8.248

4.443

10.300

0.000

15.963

4.453

22,000

2.275

0.000

3.103

0.000

6.398

4.583

8.048

0.000

17.083

3.888

24,000

4.103

0.000

2.650

0.000

4.850

4.690

5.968

0.000

14.728

2.725

26,000

7.488

0.000

3.558

0.000

2.983

4.663

6.428

0.000

10.870

2.795

28,000

12.265

0.000

7.030

0.000

1.800

4.943

7.815

0.000

8.008

2.058

30,000

16.505

0.000

9.960

0.000

1.468

5.450

7.990

0.000

1.900

3.215

32,000

20.985

0.000

9.523

0.000

1.505

7.398

6.708

0.000

0.930

2.915

34,000

21.285

0.000

7.458

0.000

2.043

11.720

6.898

0.000

0.058

4.153

36,000

11.315

0.000

5.953

0.000

2.935

15.453

6.535

0.000

0.015

3.065

38,000

2.223

0.000

3.580

0.000

2.335

10.035

3.970

0.000

0.015

4.400

40,000

0.203

0.000

1.850

0.000

0.945

3.743

2.598

0.000

0.000

2.315

42,000

0.083

0.000

0.940

0.000

0.355

1.373

1.305

0.000

0.000

1.933

44,000

0.005

0.000

0.623

0.000

0.150

0.420

1.058

0.000

0.000

1.420

46,000

0.003

0.000

0.438

0.000

0.148

0.138

0.820

0.000

0.000

1.088

48,000

0.000

0.000

0.193

0.000

0.095

0.063

1.008

0.000

0.000

1.358

50,000

0.000

0.000

0.120

0.000

0.050

0.030

2.068

0.000

0.000

0.510

52,000

0.000

0.000

0.068

0.000

0.015

0.020

0.688

0.000

0.000

0.345

54,000

0.000

0.000

0.038

0.000

0.010

0.003

0.305

0.000

0.000

0.240

56,000

0.000

0.000

0.060

0.000

0.010

0.003

0.245

0.000

0.000

0.240

58,000

0.000

0.000

0.030

0.000

0.000

0.000

0.068

0.000

0.000

0.058

60,000

0.000

0.000

0.013

0.000

0.000

0.000

0.038

0.000

0.000

0.053

62,000

0.000

0.000

0.013

0.000

0.000

0.000

0.158

0.000

0.000

0.128

64,000

0.000

0.000

0.003

0.000

0.000

0.000

0.058

0.000

0.000

0.150

66,000

0.000

0.000

0.000

0.000

0.000

0.000

0.120

0.000

0.000

0.008

68,000

0.000

0.000

0.005

0.000

0.000

0.000

0.053

0.000

0.000

0.120

70,000

0.000

0.000

0.008

0.000

0.000

0.000

0.013

0.000

0.000

0.010

72,000

0.000

0.000

0.020

0.000

0.000

0.000

0.053

0.000

0.000

0.045

74,000

0.000

0.000

0.000

0.000

0.000

0.000

0.013

0.000

0.000

0.015

76,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.015

78,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

80,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

82,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

136

Table 67. Summary of Level 2/3 Tridem Axle ALD Recommended for Arizona Rural
Principal Arterials, Non-Interstate.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

10

11

12

13

12,000

0.000

0.000

0.000

0.000

0.000

0.000

0.255

0.000

0.000

0.000

15,000

0.000

0.000

0.000

1.150

0.000

12.500

1.263

0.000

0.000

1.538

18,000

0.000

0.000

0.000

1.469

0.000

37.500

5.300

0.000

0.000

7.590

21,000

0.000

0.000

0.000

9.369

0.000

25.000

10.040

0.000

100.00

3.959

24,000

0.000

0.000

0.000

2.053

0.000

0.000

9.265

0.000

0.000

5.608

27,000

0.000

0.000

0.000

0.900

0.000

0.000

5.265

0.000

0.000

4.515

30,000

0.000

0.000

0.000

4.103

0.000

0.000

4.885

0.000

0.000

3.510

33,000

0.000

0.000

0.000

3.050

0.000

0.000

5.705

0.000

0.000

2.749

36,000

0.000

0.000

0.000

2.456

0.000

0.000

5.735

0.000

0.000

1.744

39,000

0.000

0.000

0.000

3.416

0.000

0.000

8.415

0.000

0.000

5.064

42,000

0.000

0.000

0.000

3.919

0.000

0.000

11.255

0.000

0.000

3.208

45,000

0.000

0.000

0.000

7.731

0.000

0.000

10.195

0.000

0.000

9.064

48,000

0.000

0.000

0.000

17.606

0.000

25.000

6.675

0.000

0.000

1.354

51,000

0.000

0.000

0.000

29.588

0.000

0.000

5.960

0.000

0.000

4.972

54,000

0.000

0.000

0.000

3.447

0.000

0.000

3.125

0.000

0.000

8.874

57,000

0.000

0.000

0.000

2.147

0.000

0.000

2.398

0.000

0.000

4.369

60,000

0.000

0.000

0.000

0.963

0.000

0.000

1.388

0.000

0.000

3.610

63,000

0.000

0.000

0.000

4.616

0.000

0.000

2.158

0.000

0.000

3.728

66,000

0.000

0.000

0.000

0.000

0.000

0.000

0.153

0.000

0.000

8.741

69,000

0.000

0.000

0.000

0.863

0.000

0.000

0.118

0.000

0.000

4.113

72,000

0.000

0.000

0.000

0.000

0.000

0.000

0.020

0.000

0.000

8.659

75,000

0.000

0.000

0.000

0.000

0.000

0.000

0.030

0.000

0.000

1.236

78,000

0.000

0.000

0.000

0.000

0.000

0.000

0.265

0.000

0.000

0.000

81,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

84,000

0.000

0.000

0.000

0.000

0.000

0.000

0.078

0.000

0.000

0.000

87,000

0.000

0.000

0.000

0.000

0.000

0.000

0.043

0.000

0.000

0.269

90,000

0.000

0.000

0.000

0.000

0.000

0.000

0.033

0.000

0.000

0.000

93,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.256

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.454

99,000

0.000

0.000

0.000

1.150

0.000

0.000

0.000

0.000

0.000

0.000

102,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

137

Table 68. Summary of Level 2/3 Quad Axle ALD Recommended for Arizona Rural
Principal Arterials, Non-Interstate.
Vehicle Class
8
9

Axle
Load, lb

4

5

6

7

12,000

0.000

0.000

0.000

0.000

0.000

15,000

0.000

0.000

0.000

0.000

18,000

0.000

0.000

0.000

0.000

21,000

0.000

0.000

0.000

24,000

0.000

0.000

0.000

27,000

0.000

0.000

30,000

0.000

0.000

33,000

0.000

36,000

0.000

39,000

10

11

12

13

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

100.00

0.000

0.000

0.000

1.777

0.000

0.000

0.000

0.000

0.000

0.000

7.517

0.000

0.000

0.000

0.000

0.000

0.000

15.687

0.000

0.000

0.000

0.000

0.000

0.000

0.000

9.017

0.000

0.000

0.000

0.000

0.000

0.000

100.00

4.937

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

1.967

0.000

0.000

0.000

0.000

0.000

83.333

0.000

0.000

0.930

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

9.200

42,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

5.830

45,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

13.100

48,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

2.867

51,000

0.000

0.000

0.000

7.700

0.000

0.000

0.000

0.000

0.000

5.993

54,000

0.000

0.000

0.000

11.550

0.000

0.000

0.000

0.000

0.000

2.927

57,000

0.000

0.000

0.000

36.650

0.000

0.000

0.000

0.000

0.000

6.670

60,000

0.000

0.000

0.000

32.400

0.000

0.000

0.000

0.000

0.000

0.830

63,000

0.000

0.000

0.000

11.750

0.000

0.000

0.000

0.000

0.000

0.647

66,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.450

69,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

72,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.450

75,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

78,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.327

81,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.197

84,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

87,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

90,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

93,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

96,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.457

99,000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.130

102,000

0.000

0.000

0.000

0.000

0.000

0.000

16.667

0.000

0.000

8.104

138

Traffic Geometry Inputs
Geometry inputs include a variety of measurements related to truck and traffic lanes. Table 69
shows the specific traffic inputs required under this topic.
Table 69. Traffic Geometric Inputs Required.

MEPDG Traffic
Input

Axles Per
Truck

1

Who
Collects
and
Processes
Input
MPD
National
Defaults
MPD
National
Defaults
MPD

2/3

SPR-672

AZ WIM

1

PD

WIM/AVC

2/3

SPR-672

Measured for AZ
SPR-672

Input
Level
1
2/3
1

Axle Spacing

Truck
Wheelbase
Lateral
Wander and
Offset
Dual Tire
Spacing
Average Axle
Width
Design Lane
Width

2/3

3
3
1

National
Defaults
National
Defaults
PD

How Is Input
Obtained?

How Often Is Input
Provided?

User of Input

WIM/AVC

As Requested for Project

PD

National Defaults

National Defaults

PD

WIM/AVC

As Requested for Project

PD

National Defaults

National Defaults

PD

WIM/AVC

As Requested for Project
Use 11%, 17%, and 72%
for Short (12-ft.), Medium
(15-ft.), and Long (18-ft.)
As Requested for Project
Use 15 in. and 12 in. for
Mean Wheel Location and
Standard Deviation

PD

Once

PD

Once

PD

For Specific Project

PD

National Defaults,
Use 12 in.
National Defaults,
Use 8.5 ft.
Design Plans and
Standards

PD
PD
PD

Axles per Truck
This input is defined as the mean number of axles per truck for each class of vehicle and axle
type. This input is used to compute the total number of each type of axle to pass over the design
traffic lane over the analysis period. For some trucks, such as Class 5, the number of axles is set
by the classification criteria at 2.00 single axles. For others, this value varies somewhat
depending on the definition of the classification. An analysis of Arizona data showed similar
results to the national defaults. Recommended values for axles per truck are provided below,
with quads provided from Arizona data:
Level 1: This input can be computed from WIM data for a representative number of
trucks in the design lane for a specific site. A minimum of 7 days, 24 hours per day is
recommended.
Level 2/3: Recommended values based on the national defaults and Arizona
measurements for each axle type and vehicle class are shown in Table 70.

139

Table 70. Recommended Values of Axles per Truck for Arizona Design.
Vehicle Class
Class 4
Class 5
Class 6
Class 7
Class 8
Class 9
Class 10
Class 11
Class 12
Class 13

Axle Type
Single
1.34
2.14
0.95
0.33
2.61
1.20
0.98
4.78
3.88
1.29

Tandem
0.75
0.00
0.95
0.02
0.49
1.84
1.01
0.00
0.98
1.90

Tridem
0.00
0.00
0.00
0.26
0.00
0.00
0.86
0.00
0.03
0.19

Quad
0.00
0.00
0.00
0.07
0.00
0.00
0.06
0.00
0.14
0.14

Axle Spacing
The axle spacings for tandems, tridems, and quads vary somewhat around the country. The
following national values are recommended for use in Arizona:
Tandem axles: 51.6 inches.
Tridem axles: 49.2 inches.
Quad axles: 49.2 inches.
Truck Wheelbase
This input is defined as the distance from the steering axle to the nearest axle on the truck tractor
for Classes 8 through 13. This distance varies between trucks depending on the presence of a cab
and the size of the driver’s compartment. This input has been characterized as short, medium,
and long axle spacing. The user also has to specify the percentage of trucks that have short,
medium, and long axle spacing. The MEPDG software uses this information to compute JPCP
structural responses.
For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: This input can be computed from WIM data for a representative number of
trucks in the design lane for a specific site.
Level 2/3: WIM data from LTPP were analyzed to derive percentages for trucks whose
wheelbase axle spacing, when grouped, equals the MEPDG axle spacing of 12, 15, and
18 feet. The results of the evaluation were very consistent. The percentage of trucks,
Classes 8 through 13, whose axle spacing fell within the limits are as follows:
o Short 12 ft. (10.5 to 13.5 ft): 11 percent.
o Medium 15 ft. (13.5 to 16.5 ft): 17 percent.
o Long 18 ft. (16.5 to 20 ft): 72 percent.

140

Spacing between Dual Tires
This is the center-to-center of tires on a dual axle and is set at 12 inches, based on truck
manufacturers’ information. This value was used for the national calibration of the MEPDG. It
should not be changed without a study that measures existing trucks on the highway system.
Axle Width Spacing
This is the distance from the outer wheel edge to the outer wheel edge for typical trucks. It is
determined from truck manufacturers’ information. A value of 8.5 feet was used in all of the
national calibrations. This value should be used in Arizona.
Lateral Traffic Wander
Trucks experience lateral wander as they travel down a traffic lane. This wander reduces the
number of load applications at a single point on the pavement cross section, and it affects rutting
of HMA pavements and transverse cracking of JPCP. It is characterized by a normal distribution,
a mean lateral offset on one side of the truck (that is closest to the paint stripe), and the standard
deviation:
Mean Wheel Location. This is the distance from the outer edge of the wheel to the
pavement marking, measured in inches. This value varies down a pavement project and
the mean should be used for design.
Traffic Wander Standard Deviation. The standard deviation of the lateral traffic
wander is used to estimate the number of axle load repetitions over a single point in a
probabilistic manner for predicting distress and performance. For MEPDG design at
Level 1 and Level 2/3, data collection and processing consists of the following:
o Level 1: Measurement on the highway under design is performed from an
overhead structure. Either manual or video records are made after spot-painting
dots across the traffic lane at 6-inch intervals.
o Level 2/3: The measured mean value from Arizona highways is a 15-inch mean
wheel location and 12 inches for the standard deviation.
Average Axle Width (Outside to Outside), Edge of Truck Dimensions
The actual width of the truck axles is determined from truck manufacturers or measured on
representative trucks. The value recommended for use in Arizona is 8.5 feet.
Design Lane Width (Not Slab Width for Concrete Pavement)
This is the actual width of the lane paint stripes as defined by the distance between the lane
markings on either side of the design lane. For some concrete pavements, the lane is widened 1
or 2 feet, but the paint stripes are nearly always spaced at 12 feet (a few agencies may use 13 feet
for lane width). Thus, if the slab width is 14 feet, the design lane width is 12 feet, or 144 inches.

141

For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: This width is obtained from the plans documents for the project under design.
Level 2/3: A value of 12 feet is recommended.
Other Traffic Inputs
Other traffic inputs include tire pressure and operational speed. Table 71 shows the specific
traffic inputs required under this topic.
Table 71. Other Traffic Inputs Required.
MEPDG Traffic
Input

Input
Level

Tire Pressure

3

Operational
Speed

1

Who Collects
and
Processes
Input
National
Default
PD

How Is Input Obtained?
National Default,
Use 120 psi
Use Speed Limit Unless
Steep Grade or Other Cause
to Slow Trucks Exists

How Often Is
Input Provided?

User of
Input

Once

PD

Once

PD

Tire Pressure
This is the hot inflation pressure of the tire. It is assumed that the hot inflation pressure equals
the contact pressure and is 10 percent or more above the cold inflation pressure. The tire pressure
needs to be input for both single and dual tires. The national default of 120 should be used for
this input.
Operational Speed
The truck operational speed is the mean truck speed over the highway pavement under design.
While this speed could vary somewhat from the speed limit, it is usually recommended to use the
speed limit. Variations in speed at highway speeds will not make any significant difference in the
MEPDG designs. However, there are a few critical situations where truck speed is greatly
reduced to less than 15 mph, such as long and steep grades going up a large mountain, and
intersections.
For MEPDG design at Level 1 and Level 2/3, data collection and processing consists of the
following:
Level 1: Measure the mean speed of trucks traveling along the highway at the slowest
speed location. Use this value in the design.
Level 2/3: Use the speed limit as the default value, unless the pavement is located at an
unusual speed reduction area such as a long mountain grade (15 mph recommended), or
an intersection (5 mph recommended).

142

CHAPTER 8. ACTION PLAN
The action plan described in this chapter calls for the establishment of a new traffic segment
database that includes all highways in Arizona. Alternatively, this objective could be
accomplished by expanding the current Arizona traffic database. In either case, this database
would include all traffic inputs required for the MEPDG and AASHTO 1993 design procedures.
Traffic segments would be identified by beginning and ending MP (along with GPS coordinates)
along each highway.
During the conduct of this project the MPD indicated that it was upgrading its own traffic
database and that it may be possible to incorporate the MEPDG data requirements into the
planned software implementation that is currently underway.
Table 72 summarizes the general action plan for developing a comprehensive traffic data input
system for the MEPDG. For each data input level, the table specifies who collects and processes
the input, how the input is obtained, how often the input is updated, and the user of the input.
Table 73 provides another set of recommendations for each action plan implementation step—
who, what, and when:
Responsibilities: who will do it?
Resources: funding, time, people?
Timeline: by when?
These recommendations require additional resources in terms of staffing, mainly for the analysis
of WIM data and other traffic data to prepare them for use in the MEPDG.

143

Table 72. Action Plan for Development of an ADOT Comprehensive Traffic Data Input
System for the MEPDG.
MEPDG
Traffic
Input

Volume
Inputs

Weight
Inputs

Geometry
Inputs

Other
Inputs

Input
Level

Who Collects
and
Processes
Input

How Is Input
Obtained?

How Often Is Input
Updated?

User of Input

1 On-site

MPD

AVC (perm./port.) for
Specific Project

As Requested for
Specific Project

PD, PM

2/3

MPD

AVC (Database)

Annually

PD, PM

1 On-site

MPD

WIM (perm./port.) for
Specific Project

As Requested for
Specific Project

PD

2/3

MPD

WIM: Urban, Rural,
Desert (Database)

Annually

PD

1 On-site

PD

If Used, Measured for
Specific Project

As Requested for
Specific Project

PD

2/3

PD

AZ Default (Database)

Constant or Annually

PD

1 On-site

MPD

If Used, Measured for
Specific Project

As Requested for
Specific Project

PD

2/3

MPD

AZ Default (Database)

Constant or Annually

PD

Table 73. Action Plan Summary of What, Who, and When.
Implementation Steps
(What will be done?)

Responsibilities
(Who will do it?)

Resources
(Funding/Time/People?)

Timeline
(By when?)

Develop Traffic Unit Database
(Contains all MEPDG traffic Inputs)

MPD and PD/PM (this may
be performed under current
upgrades of MPD software)

Funding: $100K
Time: 12 months
Staff: 1.5 FTE

December
2011

Volume Inputs:
*AVC Equipment
*Quality Assurance Procedures
*Analysis Procedures

MPD

Funding: MPD Ongoing
Time: MPD Ongoing
Staff: One Additional FTE

December
2011

Weight Inputs:
*WIM Equipment
*Calibration
*Quality Assurance Procedures
*Analysis Procedures

MPD

Funding: $2,500K
Annual: $90K
Time: Two years
Staff: Two additional FTE
(One WIM, One Data Analyst)

December
2013

Geometry Inputs:
*Equipment

PD

Other Inputs:

PD

Funding: None Extra
Time: None
Staff: Included in 1.5 FTE
Above
Funding: None
Time: None
Staff: Included in 1.5 FTE
above

144

December
2011

December
2011

A system for traffic data collection for the MEPDG in Arizona has been proposed and partly
developed conceptually. Inputs for Level 2/3 have been derived based on available Arizona data.
These inputs should be sufficient for most design situations.
Level 1 traffic measurement procedures have been recommended for traffic inputs, when
deemed necessary by ADOT pavement design staff. These inputs likely will not be used
often. They probably will be used with high-profile and costly projects where traffic
inputs are difficult to estimate without additional accurate information. ADOT’s traffic
data collection section will need to develop the ability to collect Level 1 on-site data in a
timely manner for requested important projects from the pavement design section.
Level 2/3 recommended inputs and defaults were prepared based on the best historical
data available. These data will need annual updates from improved traffic volume and
classification equipment, as well as from WIM sites over the next few years.
LOCATIONS OF WIM EQUIPMENT
Currently, there are two WIM sites that have been determined as capable of providing data
accurate enough for input for the MEPDG: the LTPP SPS-1 site on U.S. 93 north of Kingman,
and the LTPP SPS-2 on I-10 west of Phoenix.
There are four other WIM sites operated by the MPD that may be capable of providing good
quality data, but recent calibration results are not available, and a full series of quality assurance
checks have not been conducted, so the level of accuracy of the data has not yet been
determined. Figure 82 has been prepared along with Tables 74 through 76 to show the
recommended WIM sites to better cover the state of Arizona.

145

Figure 82. Map of Recommended WIM Sites.

146

Table 74. Recommended WIM Sites: New, Upgrades, and POEs.
Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26

Route
AZ-347
AZ-79
US-60
I-10
I-10
I-10
I-17
I-19
I-40
I-40
I-8
I-8
US-15
AZ-77
AZ-77
AZ-85
AZ-87
US-160
US-89
US-89
US-93
I-10
I-10
SL-101
SL-303
US-70

Functional Class
RMA/C
RMA/C
RMA/C
RPA-I
RPA-I
RPA-I
RPA-I
RPA-I
RPA-I
RPA-I
RPA-I
RPA-I
RPA-I
RPA-O
RPA-O
RPA-O
RPA-O
RPA-O
RPA-O
RPA-O
RPA-O
UPA-I
UPA-I
UPA-O
UPA-O
UPA-O

TTCs
6, 9, 12, 14
6, 9, 12, 14
6, 9, 12, 14
1, 2, 3
1, 2, 3
1, 2, 3
1, 2, 3
1, 2, 3
1, 2, 3
1, 2, 3
1, 2, 3
1, 2, 3
1, 2, 3
6, 9, 12
6, 9, 12
6, 9, 12
6, 9, 12
6, 9, 12
6, 9, 12
6, 9, 12
6, 9, 12
1, 2, 3
1, 2, 3
9, 12, 14
9, 12, 14
9, 12, 14

WIM Coverage Options
Upgrade 101622
New
Upgrade 100854
New
Current - Peek/Piezo
Ehrenburg POE
Current - LTPP SPSWIM - ISINC/BP
San Simon POE
New
Nogales POE
Sanders POE
New
Topock POE
Yuma POE
Upgrade 100010
New
St. George POE
Upgrade 100327
Upgrade 100800
New
New
Upgrade 100922
Current - Cardinal/Quartz
ECM w/Piezo sensors
New
Fredonia POE
Upgrade 102068
New
Kingman POE
LTPP SPSWIM - ISINC/BP
Current - TDC/Piezo
Upgrade 100139
Upgrade 101253
New
New
New
Upgrade 102024 or 102044

Table 75. Functional Class for Recommended WIM sites.
Highway Functional Class

Number of Project Sites

RMA/C
RPA-I
RPA-O

3
10
8

UPA-I
UPA-O

2
3

Table 76. Options for Meeting the Recommended WIM Site Requirements.
Options

Number of Project Sites

New

6

Upgrade
POE
Current

7
9
4

147

TYPE OF WIM EQUIPMENT
ADOT is performing an internal study to determine standard equipment for collecting WIM data.
There are several combinations of WIM controllers and in-road sensors being investigated:
TDC Systems Limited controller with piezo WIM sensors.
Cardinal Q-WIM controller with Kistler quartz sensors.
Peek ADR controller with piezo WIM sensors.
ECM Hestia controller and Kistler quartz sensors.
The MPD is also monitoring the performance of the LTPP SPSWIM site equipment, which
includes International Road Dynamics iSINC controller and bending plate technology.
To date, strong consideration has been given to the TDC and piezo WIM sensor configuration.
Since its installation, the equipment has been reliable and consistent in the weight values it has
been reporting.
To assist in the evaluation of this equipment, ARA conducted a comparison of the TDC/piezo
system with the nearby LTPP SPS-2 site for all Class 9 trucks. Since the LTPP site has been
regularly calibrated under the pooled-fund study and data analyses are performed regularly, the
data are considered to be of research quality and provided a valuable source for comparison. The
gross vehicle weight (GVW) distribution for the TDC site is shown in Figure 83. The GVW
distribution for the same data, collected by the LTPP equipment, is shown in Figure 84.

Figure 83. TDC/Piezo GVW Distribution.

148

Percentage of all class 9 vehicles

30.0%

25.0%
20.0%
15.0%
10.0%
5.0%

0.0%
8

16

24

32

40

48

56

64

72

80

88

96 104 112

Gross vehicle weight, x1000 lbs
Figure 84. LTPP SPS-2 GVW Distribution.
As illustrated in Figures 83 and 84, the TDC equipment is reporting lower weight values for the
same data. A further breakdown of the reported weights by each equipment type is shown in
Table 77. Additionally, the axle measurement for the TDC was determined, on average, to be 6.9
percent greater than the iSINC system. Axle spacing measurements are shown in Table 78.
Table 77. TDC/LTPP Weight Measurement Comparison.
Equipment

GVW (kips)

Front Axle

Tandem 1

Tandem 2

Unloaded
Peek

Loaded
Peek

LTPP (iSINC/BP)

61.5

11.2

25.6

24.6

56.0

81.0

MPD (TDC/piezo)
Difference

52.2
-15.1%

10.0
-10.7%

21.2
-17.2%

21.2
-13.8%

48.0
-14.3%

73.0
-9.9%

Table 78. Axle Spacing Measurement Comparison.
Equipment

A-B

B-C

C-D

D-E

LTPP (iSINC/BP)

17.6

4.4

32.6

4.6

MPD (TDC/piezo)

18.3

4.7

34.5

5.1

Difference

4.0%

6.8%

5.8%

10.9%

Industry standards have determined an estimate for the B-C axle spacings of 4.3 feet. As shown
in Table 78, the LTPP data are within 0.1 feet of this standard, while the TDC data are 0.4 feet
off this standard. This error is easily calibrated, however, and should not be a determining factor
in the evaluation for the Arizona standard.
Although it was expected that the TDC system would display weight measurements that were
directly related to temperature, these indications were not visible. This could mean that the TDC
is superior to other piezo WIM controllers in its ability to correlate the effects of temperature on

149

a temperature-dependent sensor, or it could mean that the ambient temperatures that were
experienced during the time the data were collected did not change significantly. Further analysis
would be required to determine if this equipment can compensate for the high effects of
temperature on the precision of piezo sensor measurements.
COST OF EQUIPMENT
When deciding to install a permanent WIM site, cost is a primary consideration. The decision to
purchase one type of WIM technology over another is a balance between system performance
accuracies and the cost of the system over its expected life cycle. The performance of the WIM
system is more a function of the in-road sensors than any other factor.
To supplement the MPD’s WIM selection study, ARA performed a cost analysis of the different
types of WIM technologies, including installation, maintenance, calibration, monitoring, and
data analyses. The information provided in Table 79 is based on one lane of sensors and does not
include costs that are associated with installation or maintenance.
Table 79. Performance and Cost of WIM Equipment.
Technology
Piezo
Quartz
Bending Plate
Load Cell

Performance

In-Road Equipment

+/- 10%
+/- 5%
+/- 3-5%
+/- 3%

$3,500
$14,500
$21,000
$60,000

Typically, the cost of the controller is related to its capabilities, so the selection of the WIM
controller should be based on the ability of the equipment to consistently deliver the collected
data to the user. Evaluations of WIM controllers and their capabilities and reliabilities are outside
the scope of this project. The range of costs for WIM controllers is approximately $12,000 to
$22,000, and there is a minimal cost difference for the controller based on the in-road sensor that
is used.
For installation, the differences in costs for one type of sensor versus another are also negligible.
However, for traffic control, the number of lane closure days required are 0.5 days per lane for
piezos and quartz, one day per lane for bending plate, and two to three days for each lane of load
cell sensors.
Regular maintenance costs (semi-annual and annual visits) among the different systems are
comparable. All require approximately the same degree of effort to assess, electronically test,
and calibrate. Unscheduled maintenance (repair) depends on the reliability of the system,
including the sensor and road condition. Based on past performance, piezo sensors have a much
shorter lifespan than load cells, but load cells are much more expensive to replace. Overall, it has
been shown that the bending plate sensor has the highest reliability and is second to the piezo in
expected life cycle repair costs. Kistler sensors are comparable with bending plates for initial
cost, but they are not as reliable. With regular maintenance, and without significant pavement
deterioration, the bending plate is a much better value.

150

Based on the experience of ARA WIM experts, the Kistler quartz sensor is recommended for
flexible roadway applications because the bending plate will often last longer than the pavement
in which it is installed. For rigid pavements, the bending plate provides the best value when
reliability, life cycle cost, and performance are prime considerations.
RECOMMENDED BUSINESS PROCESS OVERVIEW
Figure 85 illustrates the recommended business process overview for operating the MEPDG and
pavement Recommended
management systemBusiness
needs for traffic
data. Additional
details of this process are
Process
Overview
provided in Appendix G.

for MEPDG and PMS

Raw Data Files (C, W, S, 3-cards)

A - Data Collection

D – Data
Management

B – Data Processing
C – Data Reduction

A1
WIM Data

B1
Daily

A2
ATR Data

B2
Monthly

D1
Data Storage
Valid Data

D2
Data Storage
Rejedted Data

Traffic data
files
C1
Volume

C2
Class

C3
Loading
D3
Dashboard
(Data Warehouse)

Volume
data

B3
Annual

Class
Data

Valid
Data

WIM
Data
MEPDG
inputs

ESALs
growth

E1
MEPDG

E2
PMS

F – Equipment Maintenance

F1 Remote

F2 Scheduled

Calibration
Data

Maintenance
Records

F3 Repair

Repair
Records

F4 Installation

Installation
Data

E – Data Application

Figure 85. Recommended Business Process Overview.

151

D4
Maintenance
Records

152

REFERENCES
AASHTO. 1993. Guide for Design of Pavement Structures. Washington, DC: American
Association of State Highway and Transportation Officials.
AASHTO. 2008. Mechanistic-Empirical Pavement Design Guide, Interim Edition: A Manual of
Practice. Washington, DC: American Association of State Highway and Transportation
Officials.
AASHTO. 2009. Guidelines for Traffic Data Programs, 2nd Edition. Washington, DC:
American Association of State Highway and Transportation Officials.
Alavi, S. and K.A. Senn, 1999, “Development of New Pavement Design Equivalent Single Axle
Load (ESAL).” FHWA-AZ99-455. Phoenix: Arizona Department of Transportation.
Applied Research Associates, Inc. 2004. “Guide for Mechanistic-Empirical Design of New and
Rehabilitated Pavement Structures.” NCHRP Project 1-37A, Appendix AA Traffic. Washington,
DC: Transportation Research Board.
Fernandez, G. 2003. Data Mining Using SAS Applications. Boca Raton, FL: Chapman &
Hall/CRC.
FHWA. 2001. Traffic Monitoring Guide. FHWA-PL-01-021, U.S. Department of Transportation.
FHWA. 2009. LTPP Traffic Data Collection and Processing Guide, Version 1.3. FHWA-HRT09-051, U.S. Department of Transportation.
Khattree, R., and D.N. Naik. 2000. Multivariate Data Reduction and Discrimination with SAS[R]
Software. Cary, NC: SAS Institute, Inc.
Nantung, T.E., 2011, “Research Pays Off: Implementing the Mechanistic–Empirical Pavement
Design Guide for Cost Savings in Indiana.” Transportation Research News, Issue Number 271,
pp. 34-36. Washington, DC: Transportation Research Board.
SAS Institute Inc. 1999. SAS/STAT® User’s Guide, Version 8. Cary, NC: SAS Institute Inc.
Witczak, M.W. 2008. “Development of Performance Related Specifications for Asphalt
Pavements in the State of Arizona.” FHWA-SPR-08-402(2). Phoenix: Arizona Department of
Transportation.

153

154

APPENDIX A. REVIEW OF HISTORICAL ADOT TRAFFIC DATA
COLLECTION PRACTICES
The purpose of this study of ADOT traffic data collection practices is to understand how traffic
data were collected and managed and determine how coordination and sharing of traffic data can
be enhanced to maximize the usefulness of the data collection effort as related to MEPDG data
needs. The review of traffic data collection practices was performed through (1) a series of
interviews with individuals in various divisions of ADOT, and (2) assembling and reviewing
pertinent documents.
Soon after the commencement of this study, a project meeting was held with ADOT/local
agency/department staff and ARA engineers. The meeting goals included seeking information on
current statewide traffic data collection practices and identifying traffic data currently available
to ADOT. An important outcome of this meeting was to identify key personnel to be interviewed
and sources of literature containing information pertinent to this study. A list of personnel
interviewed or identified for interview is presented in Table A-1, while pertinent literature
identified and reviewed to date is presented in Table A-2. A summary of findings is presented in
the following sections.
AGENCIES WITH TRAFFIC DATA COLLECTION RESPONSIBILITY IN ARIZONA
Skszek, 2003
Several entities are responsible for gathering traffic data statewide, as presented below (Table A3 presents a listing of traffic data types collected by each entity):
ADOT Motor Vehicle Division (MVD).
ADOT Multimodal Planning Division (MPD).
ADOT Intermodal Transportation Division (ITD).
ADOT Freeway Management System (FMA).
Arizona Transportation Research Center (ATRC).
Local metropolitan planning organizations (MPOs).
Data are collected for multiple purposes, including:
Research.
Pavement design and management.
Air quality monitoring.
Vehicle size and weight enforcement.
Meeting information requests from public and private stakeholders and state governments
(e.g., meeting FHWA reporting requirements).

155

Table A-1. Literature Assembled for Review.
Title
Preliminary Engineering and Design
Manual, 3rd Edition, 1989
Five-page example print-out of pavement
management system-generated traffic
data used for AC overlay design using
SODA
Two-page ADOT Organization Chart
Three-page abstract of the report
Coordination of Commercial Vehicle
Data Collected by Automatic Traffic
Counter (ATC) and Weigh-In-Motion
(WIM) , Final Report, 2003
Implementation of the Simplified Arizona
Highway Cost Allocation Study Model,
Final Report, 2001
Update of the Arizona Highway Cost
Allocation Study, Final Report, 1999
ADOT Traffic Manual
Coordination of Commercial Vehicle
Data Collected by Automatic Traffic
Counter (ATC) and Weigh-In-Motion
(WIM), Report No. FHWA-AZ-03-526 ,
2003
Development of new pavement design
ESAL, Report No. FHWA-AZ99-455,
1999
Enhancing Arizona Department of
Transportation's Traffic Data Resource,
Report No. FHWA-AZ01-492, 2001
Cluster Analysis of Arizona Automatic
Traffic Recorder Data, Transportation
Research Record No. 1410, 1993
Estimating the Cost of Overweight
Vehicle Travel on Arizona Highways,
Report No. FHWA-AZ-06-528, 2006
Development of Design Guide Traffic
Files for ADOT (Project 11), Arizona
State University, July, 2003
Normalized Axle Load Spectra and
Pavement Design—Are the MEPDG
Default Normalized Axle Load Spectra
Inadequate? Position Paper, 15
December 2009, Applied Research
Associates, Inc.

Authors
ADOT

Literature Review Situation
Identified
Obtained Reviewed
X

X

X

X

X

X

ADOT

X

X

X

Skszek, S.L.

X

X

X

Carey, J.

X

X

X

Carey, J.

X

X

X

ADOT

X

X

X

Skszek, S.L.

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Alavi, S.H.,
and K.A.
Senn
Sterling, J., S.
Hossak, and
T. Bills
Flaherty, J.
Straus, S.H.,
and J.
Semmens
Witczak,
M.W., and Y.
Ho

Von Quintus,
H.L.

156

Table A-2. Traffic Data Types Collected by Various Agencies
in Arizona (Skszek, 2003).
Data Collection Group
ADOT Transportation
Planning Division –
Data Section
ATRC – LTPP Program
ADOT Freeway
Management System
ADOT MVD
Traffic Research &
Analysis, Inc. –
Consultant

Count
Permanent ATC

Commercial Vehicle Data Type
Class
Weight
Manual, ATC (length
Equipment not
only)
functional

ATC, WIM
ATC

ATC, WIM
WIM

WIM
Permanent ADOT sites
and portable equipment

Permanent ADOT sites
and portable equipment

WIM
None
WIM, portable and static
scales
None

Table A-3. ADOT Engineers and Other Personnel Interviewed.
ADOT/Local
Agency or
Department Staff
Dimitroplos, Christ
Bari, Javed
Burch, Paul
Delton, Jim
Hodges, Mark
Eberline, Douglas
Fregin, Ron

Agency/Department
Administrator of Arizona Transportation Research Center research and
development projects
Team Leader, ADOT Pavement Design Section
Head, ADOT Pavement Design Section
Head, ADOT Materials Section. Note that pavement design and pavement
management system groups are part of the Materials Group.
Director, Data Management and Analysis Group, Multimodal Planning
Division.
Technical Representative of Data Management and Analysis Section.
Schedule includes downloading WIM data and WIM scale installations.
Technical Representative, ADOT Pavement Management System Section.

STATEWIDE TRAFFIC MONITORING AND DATA COLLECTION
INFRASTRUCTURE
Traffic monitoring and data collection are performed using a variety of methods depending on
the entity performing the monitoring and the purpose for which data are being collected.
Methods applied statewide in Arizona include:
Coverage counts (typically 48 hours in duration).
ATRs (length classification).
Permanent vehicle classification sites (axle classification).
WIM (portable and permanent).
The following sections detail the information gathered regarding the statewide traffic monitoring
and data collection infrastructure.

157

Interview with Mark Hodges
Metropolitan Planning Organizations and other local agencies carry out approximately
4,500 short duration, mostly manual vehicle counts, annually. These counts are
performed mostly on city streets and may, in some limited instances, include vehicle
classification. ADOT verifies permanent classification sites monthly with a 60-minute
manual vehicle classification study, along with quality control checks in processing
software. Currently, field technicians verify coverage counts by watching the traffic in
the lanes and verifying the counts on the machines.
The MPD operates the following:
o One hundred seventeen-ATRs operating 24 hours a day, 7 days a week.
o One thousand two hundred short-duration counters. The duration ranges from 48
hours to 7 days.
o The MPD plans to have approximately 50 ATRs by 2011. Traffic counts and
other outputs from the AVCs are monitored monthly and verified by quality
assurance checks. Vehicle classification is performed using a vehicle
classification algorithm supplied by an AVC equipment manufacturer.
o Two WIM sites on I-10 and SR 87. The MPD plans to operate five WIM sites by
the end of 2011.
The MVD operates four WIM sites at POEs. The actual data collection and equipment
used need to be further verified.
The ATRC/MPD operates the following:
o Several WIM and AVC sites co-located with LTPP projects. It is believed that
after so many years of service, the LTPP WIM and AVC equipment are in poor
shape. In recent years, some data obtained from a few remaining LTPP sites do
not pass LTPP quality assurance checks. ADOT is considering reinstalling new,
improved WIM scales on approximately eight LTPP sites. The installation will be
on all lanes in all directions. The preferred WIM technology is the Kessler loops
(they are inductive loops of recent development).

158

Sterling et al., 2001
ADOT divides the state highway system into 1,400 segments for traffic monitoring
purposes. Each segment is identified by route and milepost and contains an identified
location for a traffic counting station.
At approximately 140 sites, ADOT collects data to classify vehicles by type. Vehicle
weight, determined by WIM equipment, is collected at seven sites, when the WIM
equipment is operational.
The majority of traffic volume counts performed by ADOT consist of either 24-hour or
48-hour counts using pneumatic road tubes or inductive loops.
On a statewide level, ADOT traffic counts begin in January in the southern part of the
state and move north throughout the year. Low-volume sections are counted every three
years.
The ADOT Traffic Studies Section uses several different mechanisms to collect the
traffic data as follows:
o ATR: in 2001, there were approximately 24 active ATRs in the state that
continuously monitor traffic 24 hours a day, each day of the year (see Table A-4
for a listing of ATR locations). ATR data are summarized to estimate daily,
monthly, and annual traffic counts.
o LTPP requires ADOT to collect WIM and AVC data. Currently, ADOT has nine
AVC sites and 16 WIM sites as part of the LTPP program (some of these have
dropped out). Table A-5 lists these sites. The data collected on these sites include
yearly truck traffic volumes reported by truck class and trucks as a percentage of
the total traffic.
The MPD used private contractors to collect traffic data for use in Small Area
Transportation Studies.
ADOT receives traffic data annually from:
o Yuma Metropolitan Planning Organization, (Yuma and Yuma County).
o Maricopa Association of Governments (Maricopa County and cities including
Phoenix, Mesa, and Glendale).
o Pima Association of Governments (Pima County and cities including Tucson).
ADOT receives traffic data infrequently from the following agencies:
o Bureau of Indian Affairs.
o Bureau of Land Management.
o National Forest Service, National Park Service.
o Tribal Governments.
Note that only traffic count data are supplied to ADOT from outside agencies. Currently
there is no procedure in place for storing the collected data other than in report form, and
no linkage exists between the outside agencies and the MPD collection efforts.
Since 1994, the MPD has undertaken a program of annual traffic counts on the entire
National Highway System in Arizona and one-third of the state highways.
In 1999, ADOT initiated the Special Counts for Air Quality and Rural HPMS project to
obtain 48-hour traffic counts at approximately 1,200 locations throughout the state, with
the assistance of contractors. The extent of traffic counts under this scheme is presented
in Table A-6.

159

Table A-4. Automatic Traffic Recorder Locations.

160

Table A-5. ADOT/ATRC LTPP AVC/WIM Sites
(Many Have Terminated Collection).

Table A-6. Traffic Counts by County.

161

In 1999, ADOT initiated the Urban Traffic Counting Project to expand its traffic data
collection efforts in the Phoenix and Tucson metropolitan areas through the collection of
24-hour counts on urban highways, ramps, and frontage roads. Traffic counts were taken
on established locations in 15-minute increments. A database was established listing
count locations, identifiers, beginning and ending times of counts, and comments. Field
data were collected using tube and loop machines, excluding those of the ADOT Freeway
Management System. Ramp and crossover counts were taken at approximately 548 sites
in the Phoenix metropolitan area and at approximately 23 sites in the Tucson urban area.
In addition, approximately 88 mainline counts were taken on state highways in the
Phoenix urban area. The counts were taken for continuous periods of 24 hours or more,
between midnight Tuesday and midnight Thursday.
In 2000, ADOT initiated a Long-Term Vehicle Classification Project to improve vehicle
classification data at approximately 65 statewide locations through 168-hour (1-week)
classification counts on the major sites (see Table A-7). The intent of the study was to
determine the magnitude of variation between 6-hour manual classifications and those of
week-long durations, especially to identify the implications for axle factors and percent
truck estimates. Preliminary results revealed essentially no differences between the 6- and
168-hour counts.
The Traffic Engineering Group has very specialized data needs on a project-by-project
basis such as turning movement counts, peak period volumes, or percentage of trucks
required for intersection design or signal phasing. As a result, this group collects
additional specific data such as turning movement counts, peak hour factors, stopped
delay, or vehicle classification. Currently, these special counts are published in the traffic
studies themselves, and there is no systematic mechanism to electronically store the
information for later use.
ADOT’s Freeway Management System collects real time data at 237 locations
throughout the greater Phoenix metropolitan freeway system. The Transportation
Technology Group manages the Freeway Management System. Collected data include
speed, volume, and occupancy. The recording devices are either inductive loops or
acoustic sensors. According to the Transportation Technology Group’s staff, up to 90
percent of the traffic recording devices do not properly report data on a continuous basis.
This situation precludes the acquisition and utilization of this data for any useful
planning, design, operation, or maintenance purposes.
In the early 2000s, the MPD maintained approximately 27 WIM stations (now there are
many fewer). The data from these WIM stations are formatted to LTPP standards and are
tabulated for hourly vehicle weights, counts, and classifications. The main goal of the
LTPP is the monitoring and evaluating of traffic data, particularly along test sections for
the evaluation of pavement conditions.

162

Table A-7. ADOT Long-Term Vehicle Classification, 2000.

163

Table A-7. ADOT Long-Term Vehicle Classification, 2000, continued.

Strauss and Semmens, 2006
ADOT POE sites collect traffic data as follows:
o Large POE facilities tend to be located on Interstates and mostly operate seven
days a week, 24 hours a day.
o Smaller/secondary POEs operate eight to 16 hours a day, five to seven days a
week. Hours of operation are determined according to traffic and/or staffing
availability.
o International POE hours of operation are determined by U.S. Customs.
o For a location of Arizona POEs, see Figure A-1.

164

Figure A-1. Arizona Port of Entry Facility Locations.
These POE facility locations are measurement tools for assessing MVD POE performance (Jason
Carey, Arizona Department of Transportation, September 2003). Several of these sites are no
longer operable.
Skszek, 2003
As of 2003, the MPD Traffic Studies Section maintained 65 ATRs and 6 WIM sites.
o Of the 65 ATR sites, only 26 were functional.
o The traffic data collected from these sites included count, speed, and length. The
length data were not classifiable into the FHWA 13-vehicle format due to the
sensor type and configuration issues.

165

o Five of the 26 sites that provided counts had one or more of the loops damaged
and needing to be replaced.
o None of the six WIM sites were functional.
The ATRC maintains 18 traffic data collection sites for LTPP (see Figure A-2). Ten of
the 18 sites are WIM sites and the remaining eight are AVCs.
o Fifteen of the 18 sites have piezo-electric sensors embedded in the pavement
surface (asphalt or concrete).
o Three sites had bending plate sensors embedded in concrete.
o Mostly, for all the sites, traffic data were retrieved monthly. For two of the high
truck volume lanes/sites, traffic data were retrieved twice monthly, or if remote
access to the site was possible and functional, then the traffic data were retrieved
weekly.
ADOT’s Freeway Management System routinely collects count, speed, and some limited
classification data from the inductive loop sensors placed roughly 0.33 miles apart along
the freeway corridor.
o Using this system, trucks could only be classified using two categories, namely:
 Trucks with lengths between 35 and 55 ft.
 Trucks greater than 55 ft long.
 The loops do not categorize trucks accurately for various reasons and
should not be used for MEPDG inputs.
The MVD has responsibility for commercial vehicle size and weight enforcement
throughout the state.
o There are 13 POE facilities that collect commercial vehicle data in support of the
MVD.
o Six of the 13 POE sites are equipped with WIM and gather count, speed, gross
and axle weight, and classification data on a continuous basis.
o The remaining seven POEs gather truck data manually through the use of static
and/or portable scales. Information is recorded on a daily basis and then reported
to the MVD on a monthly and yearly basis for statistical reviews.
o The MVD has no permanent data collection sites on highways within the interior
of the state.
MPOs collect traffic counts for certain delegated highways in Maricopa and Pima
counties using contractors. Traffic counts are performed to meet federal reporting
requirements with no differentiation made between vehicle types. Any additional traffic
data collection such as vehicle classification is performed for special studies only.

166

Figure A-2. Location of ATC and WIM Sites in Arizona in 2002.
TRAFFIC DATA FOR PAVEMENT DESIGN
Interview with Javed Bari
The current pavement design methodology (AASHTO 1993) is based on ESALs.
For ADOT pavement design, the Pavement Management System Section computes
ESALs using the pavement management system software.
ESALs are estimated using:
o The most recent estimates of AADT.
 AADT and truck percentage are usually provided by the Traffic
Engineering Group. The group typically hires a consultant to generate
volume estimates, which may include truck percentage.
 Growth factor is part of the ADOT traffic database. It is calculated as a 5year moving average of AADT. Sometimes, a growth rate as high as 6

167

percent may be reported. The highest estimate of ESALs for a 20-year
cumulative rigid ESAL historically used by ADOT is 338 million.
o 1999 vehicle classification and weight data.
 The 1999 vehicle classification and weight data are based on the results of
a study sponsored by ADOT from 1995 to 1997 (Alavi and Senn, 1999).
o Truck factors used for estimating ESALs are obtained from the Preliminary
Engineering and Design Manual (ADOT, 1989). Note that the manual was
published in 1989, while truck classification and weight data are obtained from
Alavi and Senn, published in 1999. ESALs computed using the ADOT
Preliminary Engineering and Design Manual may be significantly different than
would be calculated with current weight data.
o Truck weights used for estimating ESALs are obtained from four designated
POEs. LTPP WIM data are not used for deriving truck factors used for estimating
ESALs for ADOT.
ADOT Preliminary Engineering and Design Manual, 1989
Raw traffic data for estimating ESALs for pavement design are provided by ADOT’s
Transportation Planning Division (TPD) or the Local Government Coordination Group.
The latter provides traffic data for all urban areas with the exception of Pima (Tucson)
and Maricopa (Phoenix and suburbs) counties. Traffic data for these counties are
provided by the Pima Association of Governments and the Maricopa Association of
Governments, respectively. Traffic data for all other regions of the state are provided by
the TPD. An actual estimation of 18-kip ESALs is performed by the ADOT Materials
Group for all state highways.
The ADOT Materials Group maintains the last 10 years of traffic volume data from
which traffic volume and growth factors are calculated using regression analysis.
In 1989, the TPD had 983 ATRs located throughout the state. Traffic counts from these
ATR sites are published annually.
The TPD categorizes traffic into seven classes as follows (see Figure A-3):
o Commercial vehicles:
 Light trucks.
 Medium trucks.
 Tractor semi-trailer.
 Tractor trailer.
 Tractor semi-trailer trailer.
o Non-commercial vehicles:
 Buses.
 Automobiles.
A 5-year moving average of classification data is used to estimate the percentage
distribution among the vehicle categories.
Truck factors:
o The TPD conducts a truck weight study biennially during which a sample of the
axle weights for the 13 FHWA vehicle classes is obtained and used to generate
truck factor information needed to compute 18-kip ESALs. Actual values of truck

168

factors are determined using regression models developed using data from the
last six truck weight studies.
o Multiplying the truck factors for each vehicle type by the number of vehicles of
each type over the design period and summing it will provide the cumulative
number of 18-kip ESALs used in the design.
o These values have not been updated since the 1990s.
WIM:
o The TPD has two WIM devices that automatically sense the dynamic weight of
moving axles, estimate vehicle velocity, and classify vehicles by type.
o There are 14 POE locations where commercial vehicles are regularly weighed.
The weight data are collected and recorded manually by the MVD. The present
procedures do not offer a convenient means of using the POE truck weight data
for traffic loading estimates.

Figure A-3. ADOT Vehicle Classification Scheme.

169

170

APPENDIX B. SUMMARY OF VCD DATA USED FOR ANALYSIS
This appendix presents plots of the VCD data for projects in Arizona identified with the required
VCD data. Note that not all of the data presented in this appendix were included in the analysis,
as some data wereas deemed atypical, anomalous, or erroneous.
SectionID=4_0100

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1994
1998

1995
1999

1996
2000

Figure B-1. Plot of Vehicle Class Distribution for Site 4_0100.
SectionID=4_0100_R

Percentage of Trucks

100
90

U

80
70
60
50
40
30
20

U

10
0

U
4

5

U

U

6

7

U
8

9

U

U

U

U

10

11

12

13

Vehicle Class
YEAR

1994
1999
2005

1995
2000
U U U 2006

1996
2001
2007

1997
2003
2008

1998
2004
2009

Figure B-2. Plot of Vehicle Class Distribution for Site 4_0100_R.

171

SectionID=4_0200_R
100

Percentage of Trucks

90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1994
2007

1995
2008

1996
2009

Figure B-3. Plot of Vehicle Class Distribution for Site 4_0200_R.
SectionID=4_0500

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2003

2004

2005

2006

2007

Figure B-4. Plot of Vehicle Class Distribution for Site 4_0500.

172

SectionID=4_0500_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20

U

10
0

U
4

5

U

U

U

6

7

8

U
9

10

U

U

U

11

12

13

Vehicle Class
YEAR

1993
2001
2006

1994
2002
U U U 2007

1997
2003
2008

1998
2004

1999
2005

Figure B-5. Plot of Vehicle Class Distribution for Site 4_0500_R.
SectionID=4_0600

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

Vehicle Class
YEAR

1995

1996

Figure B-6. Plot of Vehicle Class Distribution for Site 4_0600.

173

13

SectionID=4_0600_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1994
1998
2004

1995
1999
2005

1996
2002
2007

1997
2003

Figure B-7. Plot of Vehicle Class Distribution for Site 4_0600_R.
SectionID=4_0900_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20

U

10
0

U
4

5

U

U

6

7

U
8

9

U

U

U

U

10

11

12

13

Vehicle Class
YEAR

1994
1998
2003

1995
1999
2004

1996
2000
2005

1997
2001
U U U 2007

Figure B-8. Plot of Vehicle Class Distribution for Site 4_0900_R.

174

SectionID=4_100010
100

Percentage of Trucks

90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-9. Plot of Vehicle Class Distribution for Site 4_100010.
SectionID=4_100070

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-10. Plot of Vehicle Class Distribution for Site 4_100070.

175

SectionID=4_1001

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1994
2000

1996
2005

1998
2007

Figure B-11. Plot of Vehicle Class Distribution for Site 4_1001.
SectionID=4_100139

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-12. Plot of Vehicle Class Distribution for Site 4_100139.

176

SectionID=4_100188

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-13. Plot of Vehicle Class Distribution for Site 4_100188.
SectionID=4_1001_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20

U

10
0

U
4

5

U
6

U
7

U
8

U
9

10

U
11

U

U

12

13

Vehicle Class
YEAR

1993
1997
2005

1994
1998
2006

1995
1999
2007

1996
2000
U U U 2008

Figure B-14. Plot of Vehicle Class Distribution for Site 4_1001_R.

177

SectionID=4_1002

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1998

2000

2004

2006

2007

Figure B-15. Plot of Vehicle Class Distribution for Site 4_1002.
SectionID=4_1002_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993
1999
2006

1994
2000
2007

1997
2004
2008

1998
2005

Figure B-16. Plot of Vehicle Class Distribution for Site 4_1002_R.

178

SectionID=4_100327

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-17. Plot of Vehicle Class Distribution for Site 4_100327.
SectionID=4_1003_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1994

1995

Figure B-18. Plot of Vehicle Class Distribution for Site 4_1003_R.

179

SectionID=4_100473

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-19. Plot of Vehicle Class Distribution for Site 4_100473.
SectionID=4_100537

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-20. Plot of Vehicle Class Distribution for Site 4_100537.

180

SectionID=4_100541

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-21. Plot of Vehicle Class Distribution for Site 4_100541.
SectionID=4_1006_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1995

1996

Figure B-22. Plot of Vehicle Class Distribution for Site 4_1006_R.

181

SectionID=4_1007

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1998

1999

2006

2007

Figure B-23. Plot of Vehicle Class Distribution for Site 4_1007.
SectionID=4_100767

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-24. Plot of Vehicle Class Distribution for Site 4_100767.

182

SectionID=4_1007_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20
10
0

U
4

U
5

U

U

U

6

7

8

U
9

10

U
11

U

U

12

13

Vehicle Class
YEAR

1993
1999
2004

1995
2000
U U U 2005

1996
2001
2006

1997
2002
2007

1998
2003
2008

Figure B-25. Plot of Vehicle Class Distribution for Site 4_1007_R.
SectionID=4_100800

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-26. Plot of Vehicle Class Distribution for Site 4_100800.

183

SectionID=4_100854

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-27. Plot of Vehicle Class Distribution for Site 4_100854.
SectionID=4_100922

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-28. Plot of Vehicle Class Distribution for Site 4_100922.

184

SectionID=4_101113

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-29. Plot of Vehicle Class Distribution for Site 4_101113.
SectionID=4_101248

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-30. Plot of Vehicle Class Distribution for Site 4_101248.

185

SectionID=4_1015_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993

1994

Figure B-31. Plot of Vehicle Class Distribution for Site 4_1015_R.
SectionID=4_101602

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-32. Plot of Vehicle Class Distribution for Site 4_101602.

186

SectionID=4_101622

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-33. Plot of Vehicle Class Distribution for Site 4_101622.
SectionID=4_1016_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993

1994

1995

1996

Figure B-34. Plot of Vehicle Class Distribution for Site 4_1016_R.

187

SectionID=4_1017

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2004

2005

2007

Figure B-35. Plot of Vehicle Class Distribution for Site 4_1017.
SectionID=4_1017_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993
1998
2005

1994
1999
U U U 2006

1995
2001
2007

1996
2002
2008

1997
2004

Figure B-36. Plot of Vehicle Class Distribution for Site 4_1017_R.

188

SectionID=4_101849

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-37. Plot of Vehicle Class Distribution for Site 4_101849.
SectionID=4_1018_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993

1994

1995

Figure B-38. Plot of Vehicle Class Distribution for Site 4_1018_R.

189

SectionID=4_101928

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-39. Plot of Vehicle Class Distribution for Site 4_101928.
SectionID=4_102068

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-40. Plot of Vehicle Class Distribution for Site 4_102068.

190

SectionID=4_102084

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-41. Plot of Vehicle Class Distribution for Site 4_102084.
SectionID=4_102094

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-42. Plot of Vehicle Class Distribution for Site 4_102094.

191

SectionID=4_1021_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1997

2009

Figure B-43. Plot of Vehicle Class Distribution for Site 4_1021_R.
SectionID=4_102230

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

2009

Figure B-44. Plot of Vehicle Class Distribution for Site 4_102230.

192

SectionID=4_1022_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1997

Figure B-45. Plot of Vehicle Class Distribution for Site 4_1022_R.
SectionID=4_1024

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1996

2002

2005

2006

2007

Figure B-46. Plot of Vehicle Class Distribution for Site 4_1024.

193

SectionID=4_1024_R

Percentage of Trucks

100
90

U

80
70
60
50
40
30
20
10
0

U
4

U
5

U

U

U

6

7

8

U
9

10

U

U

U

11

12

13

Vehicle Class
YEAR

1993
1999
2004

1994
2000
U U U 2005

1995
2001
2006

1996
2002
2007

1998
2003
2008

Figure B-47. Plot of Vehicle Class Distribution for Site 4_1024_R.
SectionID=4_1025

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

Vehicle Class
YEAR

2005

2006

2007

Figure B-48. Plot of Vehicle Class Distribution for Site 4_1025.

194

13

SectionID=4_1025_R

Percentage of Trucks

100
90

U

80
70
60
50
40
30
20
10
0

U

U

U

U

4

5

6

7

U
8

U
9

10

U
11

U

U

12

13

Vehicle Class
YEAR

1993
1997
2005

1994
1998
2006

1995
1999
2007

1996
2004
U U U 2008

Figure B-49. Plot of Vehicle Class Distribution for Site 4_1025_R.
SectionID=4_1034

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

Vehicle Class
YEAR

1996

1998

Figure B-50. Plot of Vehicle Class Distribution for Site 4_1034.

195

13

SectionID=4_1034_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993
1997
2001

1994
1998
2002

1995
1999
2003

1996
2000

Figure B-51. Plot of Vehicle Class Distribution for Site 4_1034_R.
SectionID=4_1036_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993

1997

Figure B-52. Plot of Vehicle Class Distribution for Site 4_1036_R.

196

SectionID=4_1037_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993

1994

1995

1996

Figure B-53. Plot of Vehicle Class Distribution for Site 4_1037_R.
SectionID=4_1062_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993

1994

1997

Figure B-54. Plot of Vehicle Class Distribution for Site 4_1062_R.

197

SectionID=4_1065_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993

1994

Figure B-55. Plot of Vehicle Class Distribution for Site 4_1065_R.
SectionID=4_6053_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993

1994

1995

1996

1997

Figure B-56. Plot of Vehicle Class Distribution for Site 4_6053_R.

198

SectionID=4_6054_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993
2004

1994
2007

2003
2008

Figure B-57. Plot of Vehicle Class Distribution for Site 4_6054_R.
SectionID=4_6055

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1996

1998

1999

2000

2001

Figure B-58. Plot of Vehicle Class Distribution for Site 4_6055.

199

SectionID=4_6055_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20

U

10
0

U
4

5

U

U

U

6

7

8

U
9

10

U
11

U

U

12

13

Vehicle Class
YEAR

1993
1999
2006

1995
2000
U U U 2007

1996
2001
2008

1997
2002

1998
2005

Figure B-59. Plot of Vehicle Class Distribution for Site 4_6055_R.
SectionID=4_6060

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

Vehicle Class
YEAR

1994

2000

2005

2006

Figure B-60. Plot of Vehicle Class Distribution for Site 4_6060.

200

13

SectionID=4_6060_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20

U

10
0

U
4

5

U
6

U
7

U
8

9

U

U

U

U

10

11

12

13

Vehicle Class
YEAR

1993
1998
2004

1994
1999
U U U 2005

1995
2000
2006

1996
2001
2007

1997
2003
2008

Figure B-61. Plot of Vehicle Class Distribution for Site 4_6060_R.
SectionID=4_7079

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

Vehicle Class
YEAR

1998

1999

2004

2005

Figure B-62. Plot of Vehicle Class Distribution for Site 4_7079.

201

13

SectionID=4_7079_R

Percentage of Trucks

100
90
80
70
60
50
40

U

U

30
20

U

10
0

U
4

U
5

6

7

U
8

9

U

U

10

11

U

U

12

13

Vehicle Class
YEAR

1993
2000
2005

1994
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure B-63. Plot of Vehicle Class Distribution for Site 4_7079_R.
SectionID=4_7613_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993
1997

1994
1998

1995
1999

1996

Figure B-64. Plot of Vehicle Class Distribution for Site 4_7613_R.

202

SectionID=4_7614

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1994
1998

1995
2003

1996
2004

Figure B-65. Plot of Vehicle Class Distribution for Site 4_7614.
SectionID=4_7614_R

Percentage of Trucks

100
90
80
70
60
50
40
30
20
10
0
4

5

6

7

8

9

10

11

12

13

Vehicle Class
YEAR

1993
1998
2003

1994
1999
2004

1995
2001
2005

1996
2002

Figure B-66. Plot of Vehicle Class Distribution for Site 4_7614_R.

203

SectionID=4_A900_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20

U

10
0

U
4

5

U

U

6

7

U
8

9

U

U

U

U

10

11

12

13

Vehicle Class
YEAR

1994
1998
2003

1995
1999
2004

1996
2000
2005

1997
2001
U U U 2007

Figure B-67. Plot of Vehicle Class Distribution for Site 4_A900_R.
SectionID=4_B900_R

Percentage of Trucks

100
90
80

U

70
60
50
40
30
20
10
0

U
4

U
5

U

U

U

6

7

8

U
9

10

U
11

U

U

12

13

Vehicle Class
YEAR

1993
1999
2004

1995
2000
U U U 2005

1996
2001
2006

1997
2002
2007

1998
2003
2008

Figure B-68. Plot of Vehicle Class Distribution for Site 4_B900_R.

204

APPENDIX C. SUMMARY OF HOURLY TRUCK DISTRIBUTION DATA
USED FOR ANALYSIS
This appendix presents plots of hourly truck distribution for Arizona projects for which these
data were available. Note that not all of the data presented in this appendix were included in the
analysis, as some data were deemed atypical, anomalous, or erroneous.
SectionID=4_100070

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure C-1. Plot of Hourly Distribution for Site 4_100070.
SectionID=4_100139

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure C-2. Plot of Hourly Distribution for Site 4_100139.

205

SectionID=4_100188

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure C-3. Plot of Hourly Distribution for Site 4_100188.
SectionID=4_100327

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-4. Plot of Hourly Distribution for Site 4_100327.

206

SectionID=4_100473

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-5. Plot of Hourly Distribution for Site 4_100473.
SectionID=4_100537

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure C-6. Plot of Hourly Distribution for Site 4_100537.

207

SectionID=4_100541

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure C-7. Plot of Hourly Distribution for Site 4_100541.
SectionID=4_100767

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure C-8. Plot of Hourly Distribution for Site 4_100767.

208

SectionID=4_100800

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-9. Plot of Hourly Distribution for Site 4_100800.
SectionID=4_100854

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-10. Plot of Hourly Distribution for Site 4_100854.

209

SectionID=4_100922

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-11. Plot of Hourly Distribution for Site 4_100922.
SectionID=4_101113

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-12. Plot of Hourly Distribution for Site 4_101113.

210

SectionID=4_101248

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-13. Plot of Hourly Distribution for Site 4_101248.
SectionID=4_101602

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-14. Plot of Hourly Distribution for Site 4_101602.

211

SectionID=4_101622

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-15. Plot of Hourly Distribution for Site 4_101622.
SectionID=4_101849

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure C-16. Plot of Hourly Distribution for Site 4_101849.

212

SectionID=4_101928

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

East

West

Figure C-17. Plot of Hourly Distribution for Site 4_101928.
SectionID=4_102068

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-18. Plot of Hourly Distribution for Site 4_102068.

213

SectionID=4_102084

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-19. Plot of Hourly Distribution for Site 4_102084.
SectionID=4_102094

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-20. Plot of Hourly Distribution for Site 4_102094.

214

SectionID=4_102230

Percentage of Trucks

15

12

9

6

3

0
0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour
Direction

North

South

Figure C-21. Plot of Hourly Distribution for Site 4_102230.
8
7

Truck Distrubtion(%)

6
5
4

2007

3

2
1
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour

Figure C-22. Hourly Truck Distribution for Site 4_0100.

215

6

Truck Distrubtion(%)

5
4
3

2007

2
1
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour

Figure C-23. Hourly Truck Distribution for Site 4_0200.

216

APPENDIX D. SUMMARY OF MAF DATA USED FOR ANALYSIS
This appendix presents plots of MAF for Arizona projects that had the required data. Note that
not all of the data presented in this appendix were included in the analysis, as some data were
deemed atypical, anomalous, or erroneous.
SectionID=4_100010

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-1. Plot of Monthly Adjustment Factor for Site 4_100010 (Vehicle Class 5).
SectionID=4_100010

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-2. Plot of Monthly Adjustment Factor for Site 4_100010 (Vehicle Class 9).

217

SectionID=4_100070

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-3. Plot of Monthly Adjustment Factor for Site 4_100070 (Vehicle Class 5).
SectionID=4_100070

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-4. Plot of Monthly Adjustment Factor for Site 4_100070 (Vehicle Class 9).

218

SectionID=4_100139

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-5. Plot of Monthly Adjustment Factor for Site 4_100139 (Vehicle Class 5).
SectionID=4_100139

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-6. Plot of Monthly Adjustment Factor for Site 4_100139 (Vehicle Class 9).

219

SectionID=4_100188

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-7. Plot of Monthly Adjustment Factor for Site 4_100188 (Vehicle Class 5).
SectionID=4_100188

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-8. Plot of Monthly Adjustment Factor for Site 4_100188 (Vehicle Class 9).

220

SectionID=4_100327

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-9. Plot of Monthly Adjustment Factor for Site 4_100327 (Vehicle Class 5).
SectionID=4_100327

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-10. Plot of Monthly Adjustment Factor for Site 4_100327 (Vehicle Class 9).

221

SectionID=4_100473

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-11. Plot of Monthly Adjustment Factor for Site 4_100473 (Vehicle Class 5).
SectionID=4_100473

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-12. Plot of Monthly Adjustment Factor for Site 4_100473 (Vehicle Class 9).

222

SectionID=4_100537

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-13. Plot of Monthly Adjustment Factor for Site 4_100537 (Vehicle Class 5).
SectionID=4_100537

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-14. Plot of Monthly Adjustment Factor for Site 4_100537 (Vehicle Class 9).

223

SectionID=4_100541

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-15. Plot of Monthly Adjustment Factor for Site 4_100541 (Vehicle Class 5).
SectionID=4_100541

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-16. Plot of Monthly Adjustment Factor for Site 4_100541 (Vehicle Class 9).

224

SectionID=4_100767

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-17. Plot of Monthly Adjustment Factor for Site 4_100767 (Vehicle Class 5).
SectionID=4_100767

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-18. Plot of Monthly Adjustment Factor for Site 4_100767 (Vehicle Class 9).

225

SectionID=4_100800

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-19. Plot of Monthly Adjustment Factor for Site 4_100800 (Vehicle Class 5).
SectionID=4_100800

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-20. Plot of Monthly Adjustment Factor for Site 4_100800 (Vehicle Class 9).

226

SectionID=4_100854

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-21. Plot of Monthly Adjustment Factor for Site 4_100854 (Vehicle Class 5).
SectionID=4_100854

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-22. Plot of Monthly Adjustment Factor for Site 4_100854 (Vehicle Class 9).

227

SectionID=4_100922

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-23. Plot of Monthly Adjustment Factor for Site 4_100922 (Vehicle Class 5).
SectionID=4_100922

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-24. Plot of Monthly Adjustment Factor for Site 4_100922 (Vehicle Class 9).

228

SectionID=4_101113

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-25. Plot of Monthly Adjustment Factor for Site 4_101113 (Vehicle Class 5).
SectionID=4_101113

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-26. Plot of Monthly Adjustment Factor for Site 4_101113 (Vehicle Class 9).

229

SectionID=4_101248

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-27. Plot of Monthly Adjustment Factor for Site 4_101248 (Vehicle Class 5).
SectionID=4_101248

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-28. Plot of Monthly Adjustment Factor for Site 4_101248 (Vehicle Class 9).

230

SectionID=4_101602

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-29. Plot of Monthly Adjustment Factor for Site 4_101602 (Vehicle Class 5).
SectionID=4_101602

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-30. Plot of Monthly Adjustment Factor for Site 4_101602 (Vehicle Class 9).

231

SectionID=4_101622

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-31. Plot of Monthly Adjustment Factor for Site 4_101622 (Vehicle Class 5).
SectionID=4_101622

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-32. Plot of Monthly Adjustment Factor for Site 4_101622 (Vehicle Class 9).

232

SectionID=4_101849

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-33. Plot of Monthly Adjustment Factor for Site 4_101849 (Vehicle Class 5).
SectionID=4_101849

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-34. Plot of Monthly Adjustment Factor for Site 4_101849 (Vehicle Class 9).

233

SectionID=4_101928

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-35. Plot of Monthly Adjustment Factor for Site 4_101928 (Vehicle Class 5).
SectionID=4_101928

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-36. Plot of Monthly Adjustment Factor for Site 4_101928 (Vehicle Class 9).

234

SectionID=4_102068

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-37. Plot of Monthly Adjustment Factor for Site 4_102068 (Vehicle Class 5).
SectionID=4_102068

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-38. Plot of Monthly Adjustment Factor for Site 4_102068 (Vehicle Class 9).

235

SectionID=4_102084

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-39. Plot of Monthly Adjustment Factor for Site 4_102084 (Vehicle Class 5).
SectionID=4_102084

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-40. Plot of Monthly Adjustment Factor for Site 4_102084 (Vehicle Class 9).

236

SectionID=4_102094

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-41. Plot of Monthly Adjustment Factor for Site 4_102094 (Vehicle Class 5).

SectionID=4_102230

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-42. Plot of Monthly Adjustment Factor for Site 4_102230 (Vehicle Class 5).

237

SectionID=4_102230

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-43. Plot of Monthly Adjustment Factor for Site 4_102230 (Vehicle Class 9).
SectionID=4_100010

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-44. Plot of Monthly Adjustment Factor for Site 4_100010 (Vehicle Class 5).

238

SectionID=4_100010

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-45. Plot of Monthly Adjustment Factor for Site 4_100010 (Vehicle Class 9).
SectionID=4_100070

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-46. Plot of Monthly Adjustment Factor for Site 4_100070 (Vehicle Class 5).

239

SectionID=4_100070

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-47. Plot of Monthly Adjustment Factor for Site 4_100070 (Vehicle Class 9).
SectionID=4_100139

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-48. Plot of Monthly Adjustment Factor for Site 4_100139 (Vehicle Class 5).

240

SectionID=4_100139

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-49. Plot of Monthly Adjustment Factor for Site 4_100139 (Vehicle Class 9).
SectionID=4_100188

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-50. Plot of Monthly Adjustment Factor for Site 4_100188 (Vehicle Class 5).

241

SectionID=4_100188

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-51. Plot of Monthly Adjustment Factor for Site 4_100188 (Vehicle Class 9).
SectionID=4_100327

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-52. Plot of Monthly Adjustment Factor for Site 4_100327 (Vehicle Class 5).

242

SectionID=4_100327

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-53. Plot of Monthly Adjustment Factor for Site 4_100327 (Vehicle Class 9).
SectionID=4_100473

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-54. Plot of Monthly Adjustment Factor for Site 4_100473 (Vehicle Class 5).

243

SectionID=4_100473

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-55. Plot of Monthly Adjustment Factor for Site 4_100473 (Vehicle Class 9).
SectionID=4_100537

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-56. Plot of Monthly Adjustment Factor for Site 4_100537 (Vehicle Class 5).

244

SectionID=4_100537

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-57. Plot of Monthly Adjustment Factor for Site 4_100537 (Vehicle Class 9).
SectionID=4_100541

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-58. Plot of Monthly Adjustment Factor for Site 4_100541 (Vehicle Class 5).

245

SectionID=4_100541

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-59. Plot of Monthly Adjustment Factor for Site 4_100541 (Vehicle Class 9).
SectionID=4_100767

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-60. Plot of Monthly Adjustment Factor for Site 4_100767 (Vehicle Class 5).

246

SectionID=4_100767

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-61. Plot of Monthly Adjustment Factor for Site 4_100767 (Vehicle Class 9).
SectionID=4_100800

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-62. Plot of Monthly Adjustment Factor for Site 4_100800 (Vehicle Class 5).

247

SectionID=4_100800

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-63. Plot of Monthly Adjustment Factor for Site 4_100800 (Vehicle Class 9).
SectionID=4_100854

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-64. Plot of Monthly Adjustment Factor for Site 4_100854 (Vehicle Class 5).

248

SectionID=4_100854

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-65. Plot of Monthly Adjustment Factor for Site 4_100854 (Vehicle Class 9).
SectionID=4_100922

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-66. Plot of Monthly Adjustment Factor for Site 4_100922 (Vehicle Class 5).

249

SectionID=4_100922

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-67. Plot of Monthly Adjustment Factor for Site 4_100922 (Vehicle Class 9).
SectionID=4_101113

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-68. Plot of Monthly Adjustment Factor for Site 4_101113 (Vehicle Class 5).

250

SectionID=4_101113

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-69. Plot of Monthly Adjustment Factor for Site 4_101113 (Vehicle Class 9).
SectionID=4_101248

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-70. Plot of Monthly Adjustment Factor for Site 4_101248 (Vehicle Class 5).

251

SectionID=4_101248

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-71. Plot of Monthly Adjustment Factor for Site 4_101248 (Vehicle Class 9).
SectionID=4_101602

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-72. Plot of Monthly Adjustment Factor for Site 4_101602 (Vehicle Class 5).

252

SectionID=4_101602

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-73. Plot of Monthly Adjustment Factor for Site 4_101602 (Vehicle Class 9).
SectionID=4_101622

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-74. Plot of Monthly Adjustment Factor for Site 4_101622 (Vehicle Class 5).

253

SectionID=4_101622

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-75. Plot of Monthly Adjustment Factor for Site 4_101622 (Vehicle Class 9).
SectionID=4_101849

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-76. Plot of Monthly Adjustment Factor for Site 4_101849 (Vehicle Class 5).

254

SectionID=4_101849

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-77. Plot of Monthly Adjustment Factor for Site 4_101849 (Vehicle Class 9).
SectionID=4_101928

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
East

JUL

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-78. Plot of Monthly Adjustment Factor for Site 4_101928 (Vehicle Class 5).

255

SectionID=4_101928

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

East

AUG

SEP

OCT

NOV

DEC

West

Month
Figure D-79. Plot of Monthly Adjustment Factor for Site 4_101928 (Vehicle Class 9).
SectionID=4_102068

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-80. Plot of Monthly Adjustment Factor for Site 4_102068 (Vehicle Class 5).

256

SectionID=4_102068

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-81. Plot of Monthly Adjustment Factor for Site 4_102068 (Vehicle Class 9).
SectionID=4_102084

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-82. Plot of Monthly Adjustment Factor for Site 4_102084 (Vehicle Class 5).

257

SectionID=4_102084

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-83. Plot of Monthly Adjustment Factor for Site 4_102084 (Vehicle Class 9).
SectionID=4_102094

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-84. Plot of Monthly Adjustment Factor for Site 4_102094 (Vehicle Class 5).

258

SectionID=4_102230

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

MAY

Direction

JUN

JUL

North

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-85. Plot of Monthly Adjustment Factor for Site 4_102230 (Vehicle Class 5).
SectionID=4_102230

Monthly Adjustment Factor

2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

JAN

FEB

MAR

APR

Direction

MAY

JUN
North

JUL

AUG

SEP

OCT

NOV

DEC

South

Month
Figure D-86. Plot of Monthly Adjustment Factor for Site 4_102230 (Vehicle Class 9).

259

260

APPENDIX E. SUMMARY OF ALD DATA USED FOR ANALYSIS
This appendix presents ALD plots for Arizona projects for which the required data were
available. Note that not all of the data presented in this appendix were included in the analysis, as
some data were deemed atypical, anomalous, or erroneous.
AXLE LOAD DISTRIBUTION PLOTS FOR CLASS 5 TRUCKS
SectionID=4_0100 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25

U

20
15
10

U

U

5
0

UU

U

3000

UUU

8000

UUUUUUUUUUUUUUUUUUUUUUUUUUUUU

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
1999
2005

1995
2000
U U U 2006

1996
2001
2007

1997
2003
2008

1998
2004
2009

Figure E-1. Plot of Single-Axle Load for Site 4_0100 (Vehicle Class 5).
SectionID=4_0100 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25

U
20

U

15

UU

10
5
0

U U
U U

UUU

3000

8000

UUUUUU

13000

18000

UUUUUUUUUUUUUUUUUUUUUU
23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
1999
2005

1995
2000
U U U 2006

1996
2001
2007

1997
2003
2008

1998
2004
2009

Figure E-2. Plot of Single-Axle Load for Site 4_0100 (Vehicle Class 9).

261

SectionID=4_0200 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
2007

1995
2008

1996
2009

Figure E-3. Plot of Single-Axle Load for Site 4_0200 (Vehicle Class 5).
SectionID=4_0200 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
2007

1995
2008

1996
2009

Figure E-4. Plot of Single-Axle Load for Site 4_0200 (Vehicle Class 9).

262

SectionID=4_0500 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25

U

20
15

U

10

U
U

5

U

0

U

UUU

UU

U

3000

8000

UU

13000

UUUU
18000

UUUUUUUUUUUUUUUUUUUUU
23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993
2001
2005

1997
2002
2006

1998
2003
2007

1999
2004
U U U 2008

Figure E-5. Plot of Single-Axle Load for Site 4_0500 (Vehicle Class 5).
SectionID=4_0500 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20

U
U U

15

U

10

U

U

5
0

UUU

3000

8000

U

U

UU

13000

UUUUUUUUUUUUUUUUUUUUUUUUUU
18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993
2001
2005

1997
2002
2006

1998
2003
2007

1999
2004
U U U 2008

Figure E-6. Plot of Single-Axle Load for Site 4_0500 (Vehicle Class 9).

263

SectionID=4_0600 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
2002

1995
2003

1996
2004

1998
2005

1999

Figure E-7. Plot of Single-Axle Load for Site 4_0600 (Vehicle Class 5).
SectionID=4_0600 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
2002

1995
2003

1996
2004

1998
2005

1999

Figure E-8. Plot of Single-Axle Load for Site 4_0600 (Vehicle Class 9).

264

SectionID=4_0900 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25

U

20

U

15
10

U

5

U

UU

0

3000

UU

8000

UUUUUUUUUUUUUUUUUUUUUUUUUUUUUU
13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
1998
2003

1995
1999
2004

1996
2000
2005

1997
2001
U U U 2007

Figure E-9. Plot of Single-Axle Load for Site 4_0900 (Vehicle Class 5).
SectionID=4_0900 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20

U

15

U

10

U

5
0

U

UU

UUUUUU

3000

8000

13000

U
UUU UU
18000

UU

UUUUUUUUUUUUUUUUUUU

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
1998
2003

1995
1999
2004

1996
2000
2005

1997
2001
U U U 2007

Figure E-10. Plot of Single-Axle Load for Site 4_0900 (Vehicle Class 9).

265

SectionID=4_1001 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1994

1995

Figure E-11. Plot of Single-Axle Load for Site 4_1001 (Vehicle Class 5).
SectionID=4_1001 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1994

1995

Figure E-12. Plot of Single-Axle Load for Site 4_1001 (Vehicle Class 9).

266

SectionID=4_1002 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1997
2005

1998
2006

1999
2007

2000
2008

2004

Figure E-13. Plot of Single-Axle Load for Site 4_1002 (Vehicle Class 5).
SectionID=4_1002 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1997
2005

1998
2006

1999
2007

2000
2008

2004

Figure E-14. Plot of Single-Axle Load for Site 4_1002 (Vehicle Class 9).

267

SectionID=4_1006 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1995

1996

Figure E-15. Plot of Single-Axle Load for Site 4_1006 (Vehicle Class 5).
SectionID=4_1006 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1995

1996

Figure E-16. Plot of Single-Axle Load for Site 4_1006 (Vehicle Class 9).

268

SectionID=4_1007 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25
20

U

15

U
U

10

U

5

U

0

UU

3000

U U
U UU

8000

UUU

13000

UUUU

18000

UUUUUUUUUUUUUUUUUUUU
23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1995
2000
2005

1996
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure E-17. Plot of Single-Axle Load for Site 4_1007 (Vehicle Class 5).
SectionID=4_1007 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25

U
20

U

15

U
U

10

U
5
0

U

UUUU

3000

U

U

8000

U
13000

UUUU
18000

UUUUUUUUUUUUUUUUUUUUUU
23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1995
2000
2005

1996
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure E-18. Plot of Single-Axle Load for Site 4_1007 (Vehicle Class 9).

269

SectionID=4_1016 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1994

Figure E-19. Plot of Single-Axle Load for Site 4_1016 (Vehicle Class 5).
SectionID=4_1016 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1994

Figure E-20. Plot of Single-Axle Load for Site 4_1016 (Vehicle Class 9).

270

SectionID=4_1017 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1997

Figure E-21. Plot of Single-Axle Load for Site 4_1017 (Vehicle Class 5).
SectionID=4_1017 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1997

Figure E-22. Plot of Single-Axle Load for Site 4_1017 (Vehicle Class 9).

271

SectionID=4_1018 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

Figure E-23. Plot of Single-Axle Load for Site 4_1018 (Vehicle Class 5).
SectionID=4_1018 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

Figure E-24. Plot of Single-Axle Load for Site 4_1018 (Vehicle Class 9).

272

SectionID=4_1021 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1997

Figure E-25. Plot of Single-Axle Load for Site 4_1021 (Vehicle Class 5).
SectionID=4_1021 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1997

Figure E-26. Plot of Single-Axle Load for Site 4_1021 (Vehicle Class 9).

273

SectionID=4_1022 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1997

Figure E-27. Plot of Single-Axle Load for Site 4_1022 (Vehicle Class 5).
SectionID=4_1022 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1997

Figure E-28. Plot of Single-Axle Load for Site 4_1022 (Vehicle Class 9).

274

SectionID=4_1024 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1998
2002
2006

1999
2003
2007

2000
2004
2008

2001
2005

Figure E-29. Plot of Single-Axle Load for Site 4_1024 (Vehicle Class 5).
SectionID=4_1024 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1998
2002
2006

1999
2003
2007

2000
2004
2008

2001
2005

Figure E-30. Plot of Single-Axle Load for Site 4_1024 (Vehicle Class 9).

275

SectionID=4_1025 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994

1996

Figure E-31. Plot of Single-Axle Load for Site 4_1025 (Vehicle Class 5).
SectionID=4_1025 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994

1996

Figure E-32. Plot of Single-Axle Load for Site 4_1025 (Vehicle Class 9).

276

SectionID=4_1034 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1995

1996

Figure E-33. Plot of Single-Axle Load for Site 4_1034 (Vehicle Class 5).
SectionID=4_1034 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1995

1996

Figure E-34. Plot of Single-Axle Load for Site 4_1034 (Vehicle Class 9).

277

SectionID=4_1036 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1997

Figure E-35. Plot of Single-Axle Load for Site 4_1036 (Vehicle Class 5).
SectionID=4_1036 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1997

Figure E-36. Plot of Single-Axle Load for Site 4_1036 (Vehicle Class 9).

278

SectionID=4_1062 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1997

Figure E-37. Plot of Single-Axle Load for Site 4_1062 (Vehicle Class 5).
SectionID=4_1062 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1997

Figure E-38. Plot of Single-Axle Load for Site 4_1062 (Vehicle Class 9).

279

SectionID=4_1065 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

Figure E-39. Plot of Single-Axle Load for Site 4_1065 (Vehicle Class 5).
SectionID=4_1065 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

Figure E-40. Plot of Single-Axle Load for Site 4_1065 (Vehicle Class 9).

280

SectionID=4_6053 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994

Figure E-41. Plot of Single-Axle Load for Site 4_6053 (Vehicle Class 5).
SectionID=4_6053 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994

Figure E-42. Plot of Single-Axle Load for Site 4_6053 (Vehicle Class 9).

281

SectionID=4_6054 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

Figure E-43. Plot of Single-Axle Load for Site 4_6054 (Vehicle Class 5).
SectionID=4_6054 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

Figure E-44. Plot of Single-Axle Load for Site 4_6054 (Vehicle Class 9).

282

SectionID=4_6055 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1996
2000
2006

1997
2001
2007

1998
2002
2008

1999
2005

Figure E-45. Plot of Single-Axle Load for Site 4_6055 (Vehicle Class 5).
SectionID=4_6055 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1996
2000
2006

1997
2001
2007

1998
2002
2008

1999
2005

Figure E-46. Plot of Single-Axle Load for Site 4_6055 (Vehicle Class 9).

283

SectionID=4_6060 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25
20

U

15

U

10
5

U

U

UU

UUU

U

0

3000

8000

U

UU

UUU

13000

UUUUUUUUUUUUUUUUUUUUUUU

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993
1999
2005

1994
2000
U U U 2006

1996
2001
2007

1997
2003
2008

1998
2004

Figure E-47. Plot of Single-Axle Load for Site 4_6060 (Vehicle Class 5).
SectionID=4_6060 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20

UU

15
10
5
0

UUU

3000

UU

U

U

UU

8000

U
U
U
13000

UUU
18000

UUUUUUUUUUUUUUUUUUUUUU
23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993
1999
2005

1994
2000
U U U 2006

1996
2001
2007

1997
2003
2008

1998
2004

Figure E-48. Plot of Single-Axle Load for Site 4_6060 (Vehicle Class 9).

284

SectionID=4_7079 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25

U

20
15

U

10

U

5

U

U

U U

0

3000

U U
U U

8000

UUU

13000

UUUUUU
18000

UUUUUUUUUUUUUUUUUUU

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993
2000
2005

1994
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure E-49. Plot of Single-Axle Load for Site 4_7079 (Vehicle Class 5).
SectionID=4_7079 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20

UU

15
10

U

U
U

U

5
0

U

UUUUU

3000

U

8000

13000

UU

UUU

18000

UUUUUUUUUUUUUUUUUUUUU
23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993
2000
2005

1994
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure E-50. Plot of Single-Axle Load for Site 4_7079 (Vehicle Class 9).

285

SectionID=4_7613 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993
1997

1994
1998

1995
1999

1996

Figure E-51. Plot of Single-Axle Load for Site 4_7613 (Vehicle Class 5).
SectionID=4_7613 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20
15
10
5
0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993
1997

1994
1998

1995
1999

1996

Figure E-52. Plot of Single-Axle Load for Site 4_7613 (Vehicle Class 9).

286

SectionID=4_7614 VehicleClass=5 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1994

1995

1996

Figure E-53. Plot of Single-Axle Load for Site 4_7614 (Vehicle Class 5).
SectionID=4_7614 VehicleClass=9 AxleType=Single

Percentage of All Axles

30

25

20

15

10

5

0
3000

8000

13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1993

1994

1995

1996

Figure E-54. Plot of Single-Axle Load for Site 4_7614 (Vehicle Class 9).

287

SectionID=4_A900 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25

U

20

U

15
10

U

5

U

UU

0

3000

UU

8000

UUUUUUUUUUUUUUUUUUUUUUUUUUUUUU
13000

18000

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
1998
2003

1995
1999
2004

1996
2000
2005

1997
2001
U U U 2007

Figure E-55. Plot of Single-Axle Load for Site 4_A900 (Vehicle Class 5).
SectionID=4_A900 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25
20

U

15

U

10

U

5
0

U

UU

UUUUUU

3000

8000

13000

U
UUU UU
18000

UU

UUUUUUUUUUUUUUUUUUU

23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1994
1998
2003

1995
1999
2004

1996
2000
2005

1997
2001
U U U 2007

Figure E-56. Plot of Single-Axle Load for Site 4_A900 (Vehicle Class 9).

288

SectionID=4_B900 VehicleClass=5 AxleType=Single

Percentage of All Axles

30
25
20

U

15

U
U

10

U

5

U

0

UU

3000

U U
U UU

8000

UUU

13000

UUUU

18000

UUUUUUUUUUUUUUUUUUUU
23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1995
2000
2005

1996
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure E-57. Plot of Single-Axle Load for Site 4_B900 (Vehicle Class 5).
SectionID=4_B900 VehicleClass=9 AxleType=Single

Percentage of All Axles

30
25

U
20

U

15

U
U

10

U
5
0

U

UUUU

3000

U

U

8000

U
13000

UUUU
18000

UUUUUUUUUUUUUUUUUUUUUU
23000

28000

33000

38000

43000

Axle Load, Ibs
YEAR

1995
2000
2005

1996
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure E-58. Plot of Single-Axle Load for Site 4_B900 (Vehicle Class 9).

289

AXLE LOAD DISTRIBUTION PLOTS FOR CLASS 9 TRUCKS
SectionID=4_0100 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25

U
20
15

U U

10

U
UUU

5
0

U

U

6000

16000

UUUU
26000

U
U U

UU

36000

UUUUUUUUUUUUUUUUUUUUU
46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1994
1999
2005

1995
2000
U U U 2006

1996
2001
2007

1997
2003
2008

1998
2004
2009

Figure E-59. Plot of Tandem-Axle Load for Site 4_0100 (Vehicle Class 9).
SectionID=4_0200 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15
10
5
0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1994
2007

1995
2008

1996
2009

Figure E-60. Plot of Tandem-Axle Load for Site 4_0200 (Vehicle Class 9).

290

SectionID=4_0500 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15

U

10

UU

U
U

5

UU

0

U

U

U

U

U

6000

16000

U

26000

UU

UUU

36000

UUUUUUUUUUUUUUUUUUUUU
46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993
2001
2005

1997
2002
2006

1998
2003
2007

1999
2004
U U U 2008

Figure E-61. Plot of Tandem-Axle Load for Site 4_0500 (Vehicle Class 9).
SectionID=4_0600 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15
10
5
0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1994
2002

1995
2003

1996
2004

1998
2005

1999

Figure E-62. Plot of Tandem-Axle Load for Site 4_0600 (Vehicle Class 9).

291

SectionID=4_0900 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20

U

15

U

10

U

U

5

UUU

0

U

6000

UUUU
16000

UUUU

U

U

26000

U
36000

UUUUUUUUUUUUUUUUUUUU
46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1994
1998
2003

1995
1999
2004

1996
2000
2005

1997
2001
U U U 2007

Figure E-63. Plot of Tandem-Axle Load for Site 4_0900 (Vehicle Class 9).
SectionID=4_1001 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

1994

1995

Figure E-64. Plot of Tandem-Axle Load for Site 4_1001 (Vehicle Class 9).

292

SectionID=4_1002 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15
10
5
0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1997
2005

1998
2006

1999
2007

2000
2008

2004

Figure E-65. Plot of Tandem-Axle Load for Site 4_1002 (Vehicle Class 9).
SectionID=4_1006 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1995

1996

Figure E-66. Plot of Tandem-Axle Load for Site 4_1006 (Vehicle Class 9).

293

SectionID=4_1007 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15
10

UUU
U

5

U

UUU

U
UU

UUU

U

0

6000

16000

26000

U

U

UU

36000

UUUUUUUUUUUUUUUUUUUU
46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1995
2000
2005

1996
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure E-67. Plot of Tandem-Axle Load for Site 4_1007 (Vehicle Class 9).
SectionID=4_1016 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

1994

Figure E-68. Plot of Tandem-Axle Load for Site 4_1016 (Vehicle Class 9).

294

SectionID=4_1017 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

1997

Figure E-69. Plot of Tandem-Axle Load for Site 4_1017 (Vehicle Class 9).
SectionID=4_1018 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

Figure E-70. Plot of Tandem-Axle Load for Site 4_1018 (Vehicle Class 9).

295

SectionID=4_1021 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1997

Figure E-71. Plot of Tandem-Axle Load for Site 4_1021 (Vehicle Class 9).
SectionID=4_1022 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1997

Figure E-72. Plot of Tandem-Axle Load for Site 4_1022 (Vehicle Class 9).

296

SectionID=4_1024 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15
10
5
0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1998
2002
2006

1999
2003
2007

2000
2004
2008

2001
2005

Figure E-73. Plot of Tandem-Axle Load for Site 4_1024 (Vehicle Class 9).
SectionID=4_1025 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1994

1996

Figure E-74. Plot of Tandem-Axle Load for Site 4_1025 (Vehicle Class 9).

297

SectionID=4_1034 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1995

1996

Figure E-75. Plot of Tandem-Axle Load for Site 4_1034 (Vehicle Class 9).
SectionID=4_1036 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

1997

Figure E-76. Plot of Tandem-Axle Load for Site 4_1036 (Vehicle Class 9).

298

SectionID=4_1062 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

1997

Figure E-77. Plot of Tandem-Axle Load for Site 4_1062 (Vehicle Class 9).
SectionID=4_1065 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

Figure E-78. Plot of Tandem-Axle Load for Site 4_1065 (Vehicle Class 9).

299

SectionID=4_6053 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1994

Figure E-79. Plot of Tandem-Axle Load for Site 4_6053 (Vehicle Class 9).
SectionID=4_6054 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

Figure E-80. Plot of Tandem-Axle Load for Site 4_6054 (Vehicle Class 9).

300

SectionID=4_6055 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15
10
5
0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1996
2000
2006

1997
2001
2007

1998
2002
2008

1999
2005

Figure E-81. Plot of Tandem-Axle Load for Site 4_6055 (Vehicle Class 9).
SectionID=4_6060 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15
10
5
0

U

U

6000

U
UU UUUUU
16000

U

U

26000

UUU
U
U
36000

UU

UUUUUUUUUUUUUUUUUUUU
46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993
1999
2005

1994
2000
U U U 2006

1996
2001
2007

1997
2003
2008

1998
2004

Figure E-82. Plot of Tandem-Axle Load for Site 4_6060 (Vehicle Class 9).

301

SectionID=4_7079 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15

U

10

U

U

5

U

U

UUU

UU

UUUU

U

0

6000

16000

26000

U

UUU

36000

UUUUUUUUUUUUUUUUUUUU
46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993
2000
2005

1994
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure E-83. Plot of Tandem-Axle Load for Site 4_7079 (Vehicle Class 9).
SectionID=4_7613 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15
10
5
0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993
1997

1994
1998

1995
1999

1996

Figure E-84. Plot of Tandem-Axle Load for Site 4_7613 (Vehicle Class 9).

302

SectionID=4_7614 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30

25

20

15

10

5

0
6000

16000

26000

36000

46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1993

1994

1995

1996

Figure E-85. Plot of Tandem-Axle Load for Site 4_7614 (Vehicle Class 9).
SectionID=4_A900 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20

U

15

U

10

U

5
0

U

UUU

U

6000

UUUU
16000

UUUU
26000

U

U

U
36000

UUUUUUUUUUUUUUUUUUUU
46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1994
1998
2003

1995
1999
2004

1996
2000
2005

1997
2001
U U U 2007

Figure E-86. Plot of Tandem-Axle Load for Site 4_A900 (Vehicle Class 9).

303

SectionID=4_B900 VehicleClass=9 AxleType=Tandem

Percentage of All Axles

30
25
20
15
10

UUU
U

5
0

U

UUU

U
UU

U

6000

16000

26000

UUU

U

U

36000

UU

UUUUUUUUUUUUUUUUUUUU
46000

56000

66000

76000

86000

Axle Load, Ibs
YEAR

1995
2000
2005

1996
2001
U U U 2006

1997
2002
2007

1998
2003
2008

1999
2004

Figure E-87. Plot of Tandem-Axle Load for Site 4_B900 (Vehicle Class 9).

304

APPENDIX F. SUMMARY OF AXLES-PER-TRUCK DATA
USED FOR ANALYSIS
This appendix presents plots of axles-per-truck data for Arizona projects that had the required
data. Note that not all of the data presented in this appendix were included in this analysis, as
some data were deemed atypical, anomalous, or erroneous.
AXLE-PER-TRUCK PLOTS FOR CLASS 5 TRUCKS
SectionID=0100

Axles per Truck

5

4

3

2

1

0
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Year
AxleType

SINGLE

Figure F-1. Plot of Axles per Truck for Site 4_0100 (Vehicle Class 5).

305

SectionID=0200

Axles per Truck

5

4

3

2

1

0
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Year
AxleType

SINGLE

Figure F-2. Plot of Axles per Truck for Site 4_0100 (Vehicle Class 5).
SectionID=0500

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-3. Plot of Axles per Truck for Site 4_0500 (Vehicle Class 5).

306

SectionID=0600

Axles per Truck

5

4

3

2

1

0
1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Year
AxleType

SINGLE

Figure F-4. Plot of Axles per Truck for Site 4_0500 (Vehicle Class 5).
SectionID=0900

Axles per Truck

5

4

3

2

1

0
1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Year
AxleType

SINGLE

Figure F-5. Plot of Axles per Truck for Site 4_0900 (Vehicle Class 5).

307

SectionID=1001

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-6. Plot of Axles per Truck for Site 4_1001 (Vehicle Class 5).
SectionID=1002

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-7. Plot of Axles per Truck for Site 4_1002 (Vehicle Class 5).

308

SectionID=1006

Axles per Truck

5

4

3

2

1

0
1995.0

1995.1

1995.2

1995.3

1995.4

1995.5

1995.6

1995.7

1995.8

1995.9

1996.0

Year
AxleType

SINGLE

Figure F-8. Plot of Axles per Truck for Site 4_1006 (Vehicle Class 5).
SectionID=1007

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-9. Plot of Axles per Truck for Site 4_1007 (Vehicle Class 5).

309

SectionID=1016

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

Year
AxleType

SINGLE

Figure F-10. Plot of Axles per Truck for Site 4_1016 (Vehicle Class 5).
SectionID=1017

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-11. Plot of Axles per Truck for Site 4_1017 (Vehicle Class 5).

310

SectionID=1018

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

Year
AxleType

SINGLE

Figure F-12. Plot of Axles per Truck for Site 4_1018 (Vehicle Class 5).
SectionID=1021

Axles per Truck

5

4

3

2

1

0
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

Year
AxleType

SINGLE

Figure F-13. Plot of Axles per Truck for Site 4_1021 (Vehicle Class 5).

311

SectionID=1022

Axles per Truck

5

4

3

2

1

0
1997

Year
AxleType

SINGLE

Figure F-14. Plot of Axles per Truck for Site 4_1022 (Vehicle Class 5).
SectionID=1024

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-15. Plot of Axles per Truck for Site 4_1024 (Vehicle Class 5).

312

SectionID=1025

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-16. Plot of Axles per Truck for Site 4_1025 (Vehicle Class 5).
SectionID=1034

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

Year
AxleType

SINGLE

Figure F-17. Plot of Axles per Truck for Site 4_1034 (Vehicle Class 5).

313

SectionID=1036

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

Year
AxleType

SINGLE

Figure F-18. Plot of Axles per Truck for Site 4_1036 (Vehicle Class 5).

SectionID=1062

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

Year
AxleType

SINGLE

Figure F-19. Plot of Axles per Truck for Site 4_1062 (Vehicle Class 5).

314

SectionID=1065

Axles per Truck

5

4

3

2

1

0
1993.0

1993.1

1993.2

1993.3

1993.4

1993.5

1993.6

1993.7

1993.8

1993.9

1994.0

Year
AxleType

SINGLE

Figure F-20. Plot of Axles per Truck for Site 4_1065 (Vehicle Class 5).
SectionID=6053

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

Year
AxleType

SINGLE

Figure F-21. Plot of Axles per Truck for Site 4_6053 (Vehicle Class 5).

315

SectionID=6054

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-22. Plot of Axles per Truck for Site 4_6054 (Vehicle Class 5).
SectionID=6055

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-23. Plot of Axles per Truck for Site 4_6055 (Vehicle Class 5).

316

SectionID=6060

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-24. Plot of Axles per Truck for Site 4_6060 (Vehicle Class 5).
SectionID=7079

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-25. Plot of Axles per Truck for Site 4_7079 (Vehicle Class 5).

317

SectionID=7613

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

1998

1999

Year
AxleType

SINGLE

Figure F-26. Plot of Axles per Truck for Site 4_7613 (Vehicle Class 5).
SectionID=7614

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Year
AxleType

SINGLE

Figure F-27. Plot of Axles per Truck for Site 4_7614 (Vehicle Class 5).

318

SectionID=A900

Axles per Truck

5

4

3

2

1

0
1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Year
AxleType

SINGLE

Figure F-28. Plot of Axles per Truck for Site 4_A900 (Vehicle Class 5).
SectionID=B900

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

Figure F-29. Plot of Axles per Truck for Site 4_B900 (Vehicle Class 5).

319

AXLE-PER-TRUCK PLOTS FOR CLASS 9 TRUCKS
SectionID=0100

Axles per Truck

5

4

3

2

1

0
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Year
AxleType

SINGLE

TANDEM

Figure F-30. Plot of Axles per Truck for Site 4_0100 (Vehicle Class 9).
SectionID=0200

Axles per Truck

5

4

3

2

1

0
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Year
AxleType

SINGLE

TANDEM

Figure F-31. Plot of Axles per Truck for Site 4_0200 (Vehicle Class 9).

320

SectionID=0500

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-32. Plot of Axles per Truck for Site 4_0500 (Vehicle Class 9).
SectionID=0600

Axles per Truck

5

4

3

2

1

0
1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Year
AxleType

SINGLE

TANDEM

Figure F-33. Plot of Axles per Truck for Site 4_0600 (Vehicle Class 9).

321

SectionID=0900

Axles per Truck

5

4

3

2

1

0
1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Year
AxleType

SINGLE

TANDEM

Figure F-34. Plot of Axles per Truck for Site 4_0900 (Vehicle Class 9).
SectionID=1001

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-35. Plot of Axles per Truck for Site 4_1001 (Vehicle Class 9).

322

SectionID=1002

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-36. Plot of Axles per Truck for Site 4_1002 (Vehicle Class 9).

SectionID=1006

Axles per Truck

5

4

3

2

1

0
1995.0

1995.1

1995.2

1995.3

1995.4

1995.5

1995.6

1995.7

1995.8

1995.9

1996.0

Year
AxleType

SINGLE

TANDEM

Figure F-37. Plot of Axles per Truck for Site 4_1006 (Vehicle Class 9).

323

SectionID=1007

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-38. Plot of Axles per Truck for Site 4_1007 (Vehicle Class 9).

SectionID=1016
5

Axles per Truck

No data available for this section.
4

3

2

1

0
1993

1994

1995

1996

Year
AxleType

SINGLE

TANDEM

Figure F-39. Plot of Axles per Truck for Site 4_1016 (Vehicle Class 9).

324

SectionID=1017

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-40. Plot of Axles per Truck for Site 4_1017 (Vehicle Class 9).
SectionID=1018

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

Year
AxleType

SINGLE

TANDEM

Figure F-41. Plot of Axles per Truck for Site 4_1018 (Vehicle Class 9).

325

SectionID=1021

Axles per Truck

5

4

3

2

1

0
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

Year
AxleType

SINGLE

TANDEM

Figure F-42. Plot of Axles per Truck for Site 4_1021 (Vehicle Class 9).
SectionID=1022

Axles per Truck

5

4

3

2

1

0
1997

Year
AxleType

SINGLE

TANDEM

Figure F-43. Plot of Axles per Truck for Site 4_1022 (Vehicle Class 9).

326

SectionID=1024

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-44. Plot of Axles per Truck for Site 4_1024 (Vehicle Class 9).
SectionID=1025

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-45. Plot of Axles per Truck for Site 4_1025 (Vehicle Class 9).

327

SectionID=1034

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

Year
AxleType

SINGLE

TANDEM

Figure F-46. Plot of Axles per Truck for Site 4_1034 (Vehicle Class 9).
SectionID=1036

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

Year
AxleType

SINGLE

TANDEM

Figure F-47. Plot of Axles per Truck for Site 4_1036 (Vehicle Class 9).

328

SectionID=1062

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

Year
AxleType

SINGLE

TANDEM

Figure F-48. Plot of Axles per Truck for Site 4_1062 (Vehicle Class 9).
SectionID=1065

Axles per Truck

5

4

3

2

1

0
1993.0

1993.1

1993.2

1993.3

1993.4

1993.5

1993.6

1993.7

1993.8

1993.9

1994.0

Year
AxleType

SINGLE

TANDEM

Figure F-49. Plot of Axles per Truck for Site 4_1065 (Vehicle Class 9).

329

SectionID=6053

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

Year
AxleType

SINGLE

TANDEM

Figure F-50. Plot of Axles per Truck for Site 4_6053 (Vehicle Class 9).
SectionID=6054

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-51. Plot of Axles per Truck for Site 4_6054 (Vehicle Class 9).

330

SectionID=6055

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-52. Plot of Axles per Truck for Site 4_6055 (Vehicle Class 9).
SectionID=6060

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-53. Plot of Axles per Truck for Site 4_6060 (Vehicle Class 9).

331

SectionID=7079

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-54. Plot of Axles per Truck for Site 4_7079 (Vehicle Class 9).
SectionID=7613

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

1998

1999

Year
AxleType

SINGLE

TANDEM

Figure F-55. Plot of Axles per Truck for Site 4_7613 (Vehicle Class 9).

332

SectionID=7614

Axles per Truck

5

4

3

2

1

0
1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Year
AxleType

SINGLE

TANDEM

Figure F-56. Plot of Axles per Truck for Site 4_7614 (Vehicle Class 9).
SectionID=A900

Axles per Truck

5

4

3

2

1

0
1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Year
AxleType

SINGLE

TANDEM

Figure F-57. Plot of Axles per Truck for Site 4_A900 (Vehicle Class 9).

333

SectionID=B900

Axles per Truck

5

4

3

2

1

0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year
AxleType

SINGLE

TANDEM

Figure F-58. Plot of Axles per Truck for Site 4_B900 (Vehicle Class 9).

334

APPENDIX G. RECOMMENDED ADOT BUSINESS PROCESS
OVERVIEW FOR MEPDG AND PAVEMENT MANAGEMENT SYSTEM

Recommended Business Process Overview
for MEPDG and PMS
Raw Data Files (C, W, S, 3-cards)

A - Data Collection

D – Data
Management

B – Data Processing
C – Data Reduction

A1
WIM Data

B1
Daily

A2
ATR Data

B2
Monthly

D1
Data Storage
Valid Data

D2
Data Storage
Rejedted Data

Traffic data
files
C1
Volume

C2
Class

C3
Loading
D3
Dashboard
(Data Warehouse)

Volume
data

B3
Annual

Class
Data

Valid
Data

D4
Maintenance
Records

WIM
Data
MEPDG
inputs

ESALs
growth

E1
MEPDG

E2
PMS

F – Equipment Maintenance

F1 Remote

F2 Scheduled

Calibration
Data

Maintenance
Records

F3 Repair

Repair
Records

F4 Installation

Installation
Data

E – Data Application

Figure G-1. Flowchart 1 for Recommended Business Process for MEPDG and Pavement
Management System.

335

Recommended Business Process Overview
for MEPDG and PMS
A1 - Automated
polling of WIM sites

Yes

A1-1
WIM Data

A1-2
Data Download

A1-3
Okay?

No

F1-1
Manual Download

W-card

A1-4
Okay?

Yes

No
D1 – Data
Storage
Valid Data

Weight
F3-2
Repair

C-card
S-card
3-card

A2-1
ATR Data

F3-1
Site Repair Order

Yes

A2-2
Data Download

A2-3
Okay?

No

F1-1
Manual Download

A2 - Automated
polling of ATR sites

A2-4
Okay?

No

F3-2
Repair

Yes

Station
Speed
Volume
Class

F3-1
Site Repair Order
B1 - Data
Processing

A - Data Collection

Figure G-2. Flowchart 2 for Recommended Business Process for MEPDG and Pavement
Management System.

336

Recommended Business Process Overview
for MEPDG and PMS
A - Data
Collection

B1 – Daily Processing of ATR and WIM Data

B1-1
Check Format

OK

B1-2
Check Binding

B1-4
Check Validity

Okay

D1 – Data
Storage
Valid Data

Error

Error

B1-5
Advanced
Analysis
Yes

Okay

Okay

Volume,
Class,
WIM Data

F1-1
Manual Download

Station
Data
Error
D2 – Data
Storage
Rejected Data

D-3-2
Repair
B1-3
Download
Okay?

B2
Monthly
Processing

B5
Annual
Processing
No

D-3-1
Site Repair Order

B - Data Processing and Quality Assurance

Figure G-3. Flowchart 3 for Recommended Business Process for MEPDG and Pavement
Management System.

337

Recommended Business Process Overview
for MEPDG and PMS

B2 – Monthly Processing of ATR and WIM Data - Volume
B1
Daily
Processing

D2 – Data
Storage
Rejected Data

Error

B2-4
Advanced
Analysis
Error

B2-1
Check for
Duplicates

Okay

B2-3
Site Records
Check

Okay

Okay

B2-5
Hourly/DOW
checks

Okay

Error

Error

Error

B2-6
Advanced
Analysis

Okay
D1 – Data
Storage
Valid Data

B2-2
Remove
duplicates

B - Data Processing and Quality Assurance

Figure G-4. Flowchart 4 for Recommended Business Process for MEPDG and Pavement
Management System.

338

Recommended Business Process Overview
for MEPDG and PMS

B2 – Monthly Processing of ATR and WIM Data - Classification
B1
Daily
Processing

D2 – Data
Storage
Rejected Data

Error

B2-10
Advanced
Analysis
Error

B2-7
Check for
Duplicates

Okay

B2-9
Volume
Checks

Okay

Error

B2-11
Class. Distr.
Checks

Okay

Error

Error

Error

B2-12
Advanced
Analysis

Okay
D1 – Data
Storage
Valid Data

B2-8
Remove
duplicates

B - Data Processing and Quality Assurance

Figure G-5. Flowchart 5 for Recommended Business Process for MEPDG and Pavement
Management System.

339

Recommended Business Process Overview
for MEPDG and PMS
B2 – Monthly Processing of ATR and WIM Data – Weigh-in-Motion

Error
B1
Daily
Processing

F1-2
Remote
Calibration

Error

B2-13
Check for
Duplicates

B2-15
Class 9 Checks

Okay

B2-16
Advanced
Analysis

D2 – Data
Storage
Rejected Data

Error

Error

B2-17
GVW Distr.
Checks

Okay

F3-1
Site Repair Order

B2-18
Unclassified
Checks
F3-2
Repair
Okay

Error

B2-14
Remove
duplicates

D1 – Data
Storage
Valid Data

B - Data Processing and Quality Assurance

Figure G-6. Flowchart 6 for Recommended Business Process for MEPDG and Pavement
Management System.

340

Recommended Business Process Overview
for MEPDG and PMS

B2 – Annual Processing of ATR and WIM Data - Station
B1
Daily
Processing

D2 – Data
Storage
Rejected Data

Error

B3-4
Advanced
Analysis
Error

B3-1
Check for
Duplicates

Okay

B3-3
Site Records
Check

Okay

Okay

B3-5
Blanks
Check

Okay

Error

Error

Error

B3-6
Advanced
Analysis

Okay
D1 – Data
Storage
Valid Data

B3-2
Remove
duplicates

B - Data Processing and Quality Assurance

Figure G-7. Flowchart 7 for Recommended Business Process for MEPDG and Pavement
Management System.

341

Recommended Business Process Overview
for MEPDG and PMS
B3
Annual
C1 – Data Reduction - Volume

C1-1
AADT

C1-2
Growth
Factors

C1-3
K Factor
D Factor

traffic.txt
trafficgrowthfactors.txt
monthlyadjustmentfactor.txt

C2 – Data Reduction - Classification

C2-1
Hourly
Distributions

C2-2
T Factor
DDF
LDF

C2-4
Class
Distributions

C2-3
MAF

vehicleclassdistribution.txt
hourlytrafficperc.txt
axlespertruck.txt

C3 – Data Reduction – Weigh-in-Motion

C3-1
Axle
Loads

C3-2
ESALs

single.alf
tandem.alf
tridem.alf
quad.alf
esals.csv

D1 – Data
Storage
Valid Data

C - Data Reduction

Figure G-8. Flowchart 8 for Recommended Business Process for MEPDG and Pavement
Management System.

342

Recommended Business Process Overview
for MEPDG and PMS
Raw Data Files

D1 – Data
Storage
Valid Data

Invalid
Data

A – Data
Collection

C – Data
Reduction

D2 – Data
Storage
Rejected Data

traffic inputs
ESALs
K, D, T factors
growth factors

traffic.txt
single.alf
tandem.alf
tridem.alf
quad.alf
vehicleclassdistribution.txt
hourlytrafficperc.txt
trafficgrowthfactors.txt
monthlyadjustmentfactor.txt
axlespertruck.txt
esals.csv

D4
Maintenance
Records

Calibration
Data

F1 Remote

B – Data
Processing

D3
Dashboard
(Data Warehouse)

Maintenance
Records

F2 Scheduled

Repair
Records

F3 Repair

Installation
Data

F4 Installation

D - Data Management

Figure G-9. Flowchart 9 for Recommended Business Process for MEPDG and Pavement
Management System.

343

Recommended Business Process Overview
for MEPDG and PMS
D3 - Dashboard

D3
Dashboard
(Data Warehouse)

traffic.txt
single.alf
tandem.alf
tridem.alf
quad.alf
vehicleclassdistribution.txt
hourlytrafficperc.txt
trafficgrowthfactors.txt
monthlyadjustmentfactor.txt
axlespertruck.txt

esals.csv
K factor
D factor
Growth factor
AADT
T factor

E1 – MEPDG
pavement design

E2 – Pavement
Management

E1
MEPDG

E2
PMS

E – Data Application
Figure G-10. Flowchart 10 for Recommended Business Process for MEPDG and Pavement
Management System.

344

Recommended Business Process Overview
for MEPDG and PMS
F3 – Unscheduled
Maintenance

F1 - Remote

B1-1
Check Format

A1-4
Okay?

Yes

A2-4
Okay?

No

Error

F2 – Scheduled
Maintenance

F2-1
Site Assessment

No
F2-2
Site Calibration

F3-1
Site Repair Order

F1-1
Manual Download

F4 - Installation

D4
Maintenance
Records

F3-2
Repair
B1-3
Download
Okay?

F4-1
Site Location

No

Error

B2-16
Advanced
Analysis

Error

F1-2
Remote
Calibration

No

A1-3
Okay?

A2-3
Okay?

F4-2
Installation Q/A

F – Equipment Maintenance

Figure G-11. Flowchart 11 for Recommended Business Process for MEPDG and Pavement
Management System.

345

Table G-1. List of Business Processes.
Box No.
A
A1
A1-1
A1-2
A1-3
A1-4
A2
A2-1
A2-2
A2-3
A2-4

Description
Data Collection
WIM Data
WIM Data Polling
WIM Data Download
Download Okay?
Manual Download Okay?
ATR Data
ATR Data Polling
ATR Data Download
Download Okay?
Manual Download Okay?
Data Processing and Quality
Assurance

Box No.
B3-2
B3-3
B3-4
B3-5
B3-6
C
C1
C1-1
C1-2
C1-3
C2

Description
Remove Duplicates
Site Records Check
Advanced Analysis
Blanks Check
Advanced Analysis
Data Reduction
Volume
AADT
Growth Factors
K, D Factors
Classification

C2-1

Hourly Distributions

B1

Daily

C2-2

B1-1
B1-2
B1-3
B1-4
B1-5
B2
B2-1
B2-2
B2-3
B2-4
B2-5
B2-6
B2-7
B2-8
B2-9
B2-10
B2-11
B2-12
B2-13
B2-14

Format Check
Binding Check
Download Okay?
Validity Check
Advanced Analysis
Monthly
Duplicate Check
Remove Duplicates
Site Records Check
Advanced Analysis
Hourly/DOW Checks
Advanced Analysis
Duplicate Check
Remove Duplicates
Volume Check
Advanced Analysis
Classification Distribution Checks
Advanced Analysis
Duplicate Check
Remove Duplicates

C2-3
C2-4
C3
C3-1
C3-2
D
D1
D2
D3
D4
E
E1
E2
F
F1
F1-1
F1-2
F2
F2-1
F2-2

B2-15

Class 9 Checks

F3

B2-16
B2-17
B2-18
B3
B3-1

Advanced Analysis
GVW Distribution Checks
Unclassified/Class 15 Checks
Annual
Duplicate Check

F3-1
F3-2
F4
F4-1
F4-2

B

346

T Factor, Design Direction
Factor, Design Lane Factor
Monthly Adjustment Factors
Class Distributions
Weigh-in-Motion
Axle Loads
ESALs
Data Management
Data Storage – Valid Data
Data Storage – Rejected Data
Dashboard (Data Warehouse)
Maintenance Records
Data Application
MEPDG Pavement Design
Pavement Management
Equipment Maintenance
Remote Maintenance
Manual Download
Remote Calibration
Scheduled Maintenance
Site Assessment
Site Calibration
Unscheduled Maintenance
(Repair)
Site Repair Order
Site Repair
Installation
Site Location
Site Installation Q/A