ARIZONA DEPARTMENT OF TRANSPORTATION REPORT NUMBER: FHWA-AZ90-322 FORENSIC PAVEMENT ANALYSIS Final Report Prepared by: Maralou De Nicholas, Ph.D. Center for Advanced Research in Transportation, Cdtege of Engineering 81Applied Sciences Arizona State University Tempe, Arizona 852874306 April 1990 Prepared for: Arizona Department of Transportation 206 South 17th Avenue Phoenk, Arlzona 85007 In cooperation with U.S. Department of Transportation Federal Highway Administration The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Arizona Department of Transportation or the Federal Highways Administration. This report does not constitute a standard, specification, or regulation. Trade or manufacturer's names which 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 FHWA-AZ90- 322 4. Title and Subtitle I 3. Recipient's Catalog NO. 2. Government Accession No. 1. Report No. I 1 5. Reporl Dale FORENSIC PAVEMENT ANAtYSIS 8. Performing Organization Report NO. 7. Author (s) DR. MARALCU N I C H O L A S I I 10.Work Unit No. 9. Pedorming Organization Name and Address I ( X N l E R FOR ADVANCED RESEARCH I N TRANSPORTATION ARIZONA STATE UNIVEFSITY TEMPE, AZ 85287 . 11. Contract or Grant No. c 13. Type of Report & Period Covered 12. Sponsoring Agency Name and Address ARIZONA DEPARTMENT OF TRANSPORTATlON 206 S. 17TH AVENUE PHOENIX, ARIZONA 85007 14. Sponsoring Agency Code I I 15. Supplementary Notes Prepared in cooperation with the U.S. Department of Transportation, Federal Highway Admlnlstratlon I 16. Abstract This s t d y proposed t o use portable weigh-in-motion systems t o c o l l e c t sample truck d a t a throughout the State of Arizona i n l i e u of standard loadmeter t e s t i n g . The primiq purpose of data collection w a s t o provide a large quantity of useful data f o r input i n t o the pavement design process. It was also anticipated t h a t the data would be helpf u l t o s t a t e highway planners. Originally, data w e r e t o be collected at t h i r t y s i t e s on the Arizona S t a t e Highway System. The sites were selected by knowledgeable Arizona Deparhnent of Transportation ( A m ) personnel in order t o increase t h e probability of obtaining a representative sample of truck t r a f f i c on Arizona's highways. Portable W I M Devices wre evaluated f o r various applications d t h a t evaluation is contained in t h i s report. 123.Registrant's Seal 1 18. Distribution Statement 17. Key Words L 19. Security Classification (of this report) Unclassified I Document is available to the U.S. public through the National Technical Information Service. Springfield. Virginia 22161 21. No. of Pages 20. Security Classification (of this page) 1 Unclasslied 1 209 ( 22. Price I Acknowledgments This project could not have been completed without the utmost in patience and cooperation from Arizona Department of Transportation's Transportation Planning Division. Lou Schmitt, Deputy Director, is responsible for the project concept. Without that original idea, this project never would have been. E d Green, Manager of the Travel and Facilities Branch of TPD during the implementation of this project, used his considerable expertise and knowledge of the State Highway System to select the 30 sites for data collection. H e spent a good deal of his time guiding this project and helping me direct the field crews in the installation of equipment and collection of data. This project was fraught with unforeseen problems: bad weather, equipment malfunctions, and other on-site catastrophes. I was very fortunate to have two electronic wizards to work with on this project: Denis Duman and Phylos Lame. I can't express how much their tireless dedication and sense of humor contributed to this project. This research was administered by ADOT's Transportation Research Center. I appreciate the time and effort expended by Bob Pike and Frank McCullagh, Director, to keep up with progress on the project and accommodate the many setbacks we encountered. I also am grateful to Liz Kuproski for the many times she dropped everything to help me with the project budget and paperwork. Finally, I wish to thank E. Todd Eure, Graduate Assistant in CART and Virgil Sheets, Graduate Associate in the Department of Psychology for the role they played in data reduction and analysis. They were both vaIuable contributors to this research effort. Table of Contents Page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v. INTRODUCIION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 Weigh-In-Motion: The Alternative . . . . . . . . . . . . . . . . . . . . . . . . . 2. RESEARCH PURPOSE AND SCOPE . . . . . . . . . . . . . . . . . . . . . . . . . . .2 List of Tables List of Figures WEIGH IN MOTION SYSTEM DESCRIITION . . . . . . . . . . . . . . . . . . . . .3 TESTRESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6 . System Calibration and Pretesting . . . . . . . . . . . . . . . . . . . . . . . . . . 6. Reliability Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7 Validity Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7. Vehicle Classification Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 . STUDY RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Frequency Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14 Weight Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25 Equipment Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28 DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30 RECOMMENDATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32 APPENDICES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33 APPENDIX A: Vehicle Classification Scheme . . . . . . . . . . . . . . . . . .34 APPENDIX B: WIM Data Collection Sites . . . . . . . . . . . . . . . . . . . .39 APPENDIX C: Frequency Data for Individual Sites . . . . . . . . . . . . . . - 4 2 APPENDIX D: Automatic Traffic Recorder Data . . . . . . . . . . . . . . . . 91 APPENDIX E: Descriptive Statistics for Individual Sites . . . . . . . . . . . 105 APPENDIX F: Statistical Analysis Tables . . . . . . . . . . . . . . . . . . . . 154 APPENDIX G: Site Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 List of Tables Table 1 Descriptive statistics for two weigh-in-motion systems 2 Descriptive statistics for WIM and static scales . . . . . . . . . . . . . .9 3 Vehicle classification scheme 4 Vehicle classification data 5 Automatic traffic recorder data 6 Frequency adjustments by site and direction 7 Mean gross and steering axle weights by vehicle class Page . . . . . . . . . .8 . . . . . . . . . . . . . . . . . . . . . . . 11 . . . . . . . . . . . . . . . . . . . . . . . . .16 . . . . . . . . . . . . . . . . . . . . . . 19 . . . . . . . . . . . . . . 22 . . . . . . . . . 26 List of Figures Figure Page 1 Locations of proposed sites for WIM data collection . . . . . . . . . . .4 2 Diagram of weigh-in-motion installation 3 Raw data output 4 Automatic traffic recorder locations 5 Adjusted daily truck volumes by WIM site 6 Mean gross weight by route 7 Mean gross weight by machine type by route . . . . . . . . . . . . . . . . . 5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13 . . . . . . . . . . . . . . . . . . . 18 . . . . . . . . . . . . . . . 24 . . . . . . . . . . . . . . . . . . . . . . . . 27 . . . . . . . . . . . . . . 29 FORENSIC PAVEMENT ANALYSIS INTRODUCTION Despite an increase in maintenance activity and expenses on the Arizona state highway system over the past decade, the condition of the system continues to decline. In some locations, the pavement is deteriorating faster than its design life span. There are many reasons for this deterioration. Rutting, for example, may be caused by a combination of factors, including bad weather (moisture), traffic conditions (e.g., heavy trucks), and several other variables. While it may not be possible to calculate the impact of mmy of these factors, it is essential to the pavement design process to assess the extent of heavy vehicle traffic on the state system. Until now, the sole source of heavy vehicle load data has been from standard loadometer tests. These tests have been conducted every two years at 14 locations on the state system using a portable platform scale. Although it is desirable that the data be collected more frequently and at additional points along the system, the difficulty in using the portable scales and the accompanying risks to ADOT personnel restrict the scope of testing and confine the tests to daytime hours. It is likely, then, that the data collected during these tests are underestimates, as much of the heavier truck traffic is thought to occur at night. In addition, the communication of heavy vehicle drivers with one another may lead to avoidance of the test site by overweight vehicles, further adding to the systematic error in measurement. In order to more accurately assess traffic mix, volumes, and loads on the system, it is clear that large amounts of data would need to be collected system-wide over full 24-hour periods. Preferably, the data would be collected using a less obtrusive means, so that systematic error could be avoided. Weigh-In-Motion: The Alternative Past studies have demonstrated the viability of weigh-in-motion (WIM) systems for traffic measurement (1,2). The suitability of these systems specifically for collecting highway design and planning data was explored by the State of Louisiana (3). In an 18-month long study, data were collected at two locations proximal to static scales operated by Louisiana Department of Transportation and Development. Statistical analyses conducted on the data comparing static, weigh-in-motion, and portable scales generally found very high correlations between the different weighing methods. Although the portable and static scales differed least from each other, weigh-in-motion scales deviated only slightly more. The study concluded that WIM equipment could be used to supplement or replace loadometer study methods. Portable WIM systems were suggested for this purpose. Thus, it appears that weigh-in-motion technology provides the tools necessary to accomplish the extensive data collection effort required for effective pavement design. With the use of WIM equipment and loop detectors, the number and classification of heavy vehicles, as well as their weight, can be assessed electronically. WIM equipment can provide all of the data which is currently being supplied by loadometer tests for input into the pavement design process. Portable weigh-in-motion systems have the added advantage of being able to be installed in a relatively short period of time, by a small crew, with minimal traffic interruption. RESEARCH PURPOSE AND SCOPE This study proposed to use portable weigh-in-motion systems to collect sample truck data throughout the State of Arizona in lieu of standard loadometer testing. The primary purpose of data collection was to provide a large quantity of useful data for input into the pavement design process. It was also anticipated that the data would be helpful to state highway planners. Originally, data were to be collected at thirty sites on the Arizona State Highway System. The sites were selected by knowledgeable Arizona Department of Transportation (ADOT) personnel in order to increase the probability of obtaining a representative sample of truck traffic on Arizona's highways. The locations of the proposed sites are depicted in Figure 1. As can be seen, the selected data collection points are primarily on Interstate routes, as these routes are known to carry the majority of the State's truck traffic. (Note that the site numbers do not carry any special significance -- they merely serve as identifiers.) At each site, the plan was to install the WIM equipment in one lane in each direction of travel. The equipment would then be left to collect data for a full 24 hour period. It was anticipated that the data couId be collected and analyzed in a six-month time frame. WEIGH IN MOTION SYSTEM DESCRIPTION The weigh-in-motion systems used in this study were manufactured by Golden River; the mats were manufactured for Golden River by Electromatic in South Africa. The Model 381 systems which were utilized have 128K memory for data storage. In a typicaI installation, the WIM system is either connected to existing speed loops embedded in the pavement or, if these are not available, to temporary loops affixed to the pavement with adhesive tape. (See diagram in Figure 2.) When a vehicle passes over the mat, its speed, classification, axle spacings, length, axle weights and gross weight are calculated and stored in memory with a unique id number and the time and date. Once retrieved, data are easily transferred to microcomputer for processing. @ Interstate Highays Other State Highways WIM Sita/Nurnber Figure 1. Locations of proposed sites for WIM data collection. TEST RESULTS System Calibration and Pretesting The weigh-in-motion mats are calibrated prior to shipment based on the results of factory tests. However, the preset correction factor usually requires adjustment once the WIM equipment is placed in the field in order to accommodate heavy vehicle traffic. Techniques for calibrating WIM systems vary considerably, as noted by Davies and Sommerville (4). The method used to calibrate the WIM equipment in this study is similar to the technique they described which is used by Idaho Department of Transportation: Essentially, it involved using a three-axle test vehicle of 30,000 Ib. gross weight making a series of runs over the systems of 20, 40, and 60 mph. The system calibration was then adjusted to minimize the average differences between the dynamic and static gross weights (p. 123). A variation of the "known weight" method was used in this study. Two trucks were used for calibration -- one two-axle and one three-axle. A minimum of ten runs were made over the WIM mats by each vehicle at a constant rate of speed. It was discovered that one mat operated properly with the factory correction factor of 207. The second mat tested, which had a preset correction factor of 157, was calibrated to a correction factor of 132. / As is the case when using any measurement tool, it was deemed important to initially assess the accuracy of the Golden River weigh-in-motion systems. For that reason, a thorough test was conducted in order to assess the validity (accuracy compared to static weight) and reliability (accuracy compared to other WIM systems) of the WIM equipment used in this study. The tests were conducted over two days in late September, 1988. Two sets of WIM equipment were installed side by side on the onramp to the weigh station at Topock Table 1. Descriptive statistics for two weigh-in-motion systems. Group Mean Gross Wt Standard Deviation Standard Error 95 Percent Confidence Interval for Mean WIM 1 59103.34 18753.16 2151.13 54818.06 To 63388.62 WIM 2 56369.37 19534.05 2240.71 51905.65 To 60833.09 Total 57736.35 19133.30 1551.92 54670.08 To 60802.63 Group Minimum Maximum WIM 1 13485 85140 WIM 2 9315 86733 Total 9315 86733 Table 2. Descriptive statistics for WIM and static scales. Standard Error 95 Percent Confidence Interval for Mean 19133.30 1551.92 54670.08 To 60802.63 59564.74 19940.01 2287.28 55008.25 To 64121-22 58345.82 19381.20 1283.55 55816.62 To 60875.01 Group Minimum Maximum WIM 9315 86733 Static 17230 83330 Total 9315 86733 Group Mean Gross Wt Standard Deviation WIM 57736.35 Static Total Vehicle Classification Test The Golden River WIM system classifies vehicles based on the number of axles and the length of the spacing between them. Vehicles are classified according to Federal Highway Administration Scheme F. This vehicle classification scheme is summarized in Table 3 and presented in detail in Appendix A. For the purpose of this study, the WIM systems were set to collect and record data for all vehicles class 5 (2-axle, 6-tire single unit trucks) and above. It should be noted that if the WIM system does not recognize the axle configuration of a vehicle it assigns it a class of 13. Thus, any vehicle classed as 13 that does not have 7 or more axles is considered an error and should be discarded from the data set. Some errors in classification were noticed to occur during the validity and reliability test phase of the study. Four errors were observed in data from the downstream mat. The errors were in pairs, and appeared to result from the inability of the equipment to distinguish the end of one vehicle and the beginning of another. These errors represented only 5% of the data. A more serious problem was observed in data from the upstream mat. Eleven classification errors were detected; five of these were failures of the equipment to identify the vehicle based on axle configurations (class of 13 was assigned). In the other six cases, the equipment assumed an extra axle and assigned the next highest class. Errors colnprised 14% of the data for this equipment. These classification errors were assumed to be an inherent feature of the portable WIM system. As other aspects appeared to be functioning properly and no error codes were generated during the test, the occasional misclassification of vehicles was accepted with misgivings. Table 3. Vehicle classification scheme. Vehicle Classification 1 Vehicle Tvue Motorcycles Passenger cars (including those hauling recreational trailers) Two-axle, 4-tire pickups, vans, motor homes (including those with recreational trailers) Buses 5 Two axle, 6-tire single unit trucks 6 Three axle single unit trucks 7 Four or more axle single unit trucks 8 Four or less axle single trailer trucks 9 Five axle single trailer trucks 10 Six or more axle single trailer trucks 11 Five or less axle multi-trailer trucks 12 Six axle multi-trailer trucks 13 Seven or more axle multi-trailer trucks STUDY RESULTS The data collection began in July 1988 and was scheduled for completion in mid-October 1988. It became apparent almost immediately that this time frame was unrealistic. WIM sites could be completed at a rate of only one or two sites per week. In addition, the WIM equipment experienced failures and manifested data errors that became more frequent as time went on. By the targeted data collection deadline, only eight sites had been completed. Approximately 6 additional months were thus added to the study to complete data collection, and malfunctioning pieces of equipment were replaced with new units. It was decided, in conjunction with ADOT management, that five low-priority sites (7, 14, 16, 17, and 21) could be dropped from the study with little consequence. Data were collected at the remaining 25 sites. It was discovered that the equipment had malfunctioned at site 4; the resulting data were unusable and the site was eliminated from analyses. The main criterion for selection of the highway segment to install the WIM equipment was pavement smoothness and absence of rutting. Whenever possible, curves and grades were avoided, as were areas where vehicles might tend to accelerate or decelerate. The route and milepost settings for each site, the equipment used, and the date that data were collected are presented in Appendix B. At each site, data were collected for 24 consecutive hours in one lane on each side of the highway. WIM mats were placed in the right-hand lane on each side, as it is estimated that the majority of heavy vehicle traffic utilizes this lane. WIM equipment was set to record the weight of vehicles class 5 and above (2D and larger). WIM data at each site were retrieved from system memory to microcomputer. A sample of raw data output is presented in Figure 3. The data were subjected to extensive editing to remove blank lines, headings and extraneous characters s o that they could be analyzed using SPSS/PC+ statistical software. Descriptive statistics were generated for *BEG11 47 01 018100!4 Q 6.5 0 B!!i7 030 O *SEp DATE IME SPO CL C [.EN6 UEtI.TY [OT RXLEl AY,LE2 kXLE3 AXI.E4 AXLE5 AXLEG AXLE7 t?V,CEB hXiE9 BXLlF kXCll fix112 AXL13 *AKLE SEPkPRTIDH 711111. !-? 2-3 3-4 4-5 5-5 6-7 7-8 8-9 9-1010-1111..1?12-13 Figure 3. Raw data output. each site in each direction. The sites were then aggregated into one database for further examination. Prior to conducting inferential analyses, an attempt was made to eliminate vehicles that were misclassified. With guidance from knowledgeable ADOT personnel, the following vehicles were eliminated: .. .. 65 Class 13s with less than 7 axles 312 Class 13s with more than 333 Class 13s with a length of less than 50 feet 110 Class 13s with a length of more than 75 feet. In addition, 61 vehicles were deleted with recorded gross weights or steering axle weights of zero. The edited database used in analysis consisted of 54,813 vehicles class 5 and above. Frequency Analysis Raw frequency data for individual sites are presented in Appendix C. Before sites could be compared with one another, several adjustments to the data were required. First, there were a few sites at which it was not possible to collect a full 24 hours of data. The frequencies for these sites were divided by the fraction of 24 hours that they represented to make them comparable to the 24 hour counts at other sites. (For example, if data were only collected at a given site from 12 midnight to 12 noon of the following day, the frequency would be divided by .5, or the ratio of 12 to 24 hours. In this example, it is easy to see that dividing by .5 produces the same result as multiplying the count by 2.) It may be recollected that data were only collected in one lane of travel for each direction at a given site. Because nearly all of the chosen sites had two lanes in each direction, the frequencies had to be adjusted for number of lanes. For this purpose, 24 hour classification counts were taken at 15 designated WIM sites. The percentage of vehicles class 5 and above traveling in the outside lane was calculated (Table 4), and these were used to estimate total volumes at each site. At sites where classification data were not collected, the closest classification point was used for the adjustment. For remote sites 14 for which no classification data were available (1 South, 30 North and South) a 90%-10% lane split in truck traffic was assumed. Knowing that traffic varies on different days of the week, it was considered desirable to attempt to "normalize" the frequency counts across days of the week so that a more appropriate comparison between sites might be accomplished. Unfortunately, classification data were only available for a 24-hour period at some sites, not the 7-day, 24-hour counts that were anticipated. For this reason, automatic traffic recorder (ATR) data for 1988 were used to adjust the data for day of the week*. A listing of ATR locations that were used to adjust the WIM frequencies is presented in Table 5. A map of ATR locations is depicted in Figure 4. Divisor factors were arrived at by dividing the average 12-hour count for the day of week data were collected by the weekly average 12-hour count (see Appendix D). *Note: ATR data are not broken down by vehicle classification, and are thus a representation of all traffic at a given location. The author recognizes that truck traffic patterns may differ from those of other vehicles, so that using a11 traffic to adjust truck traffic volumes for day of the week may be inducing bias at some sites. Table 4. Vehicle classification data WIM Site 1 Direction North South Classification Site Used None % Trucks in Outside Lane 100 90* 2 East West 2 93 89 3 East West 3 86 89 5 East West 5 86 89 6 East West 6 81 72 8 East West 8 79 81 9 East West 8 79 81 10 East West 10 92 93 II East West 10 92 93 12 East West 10 02 93 13 East West 15 83 84 15 East West 15 83 84 18 East West 18 62 79 19 North South 19 92 86 20 East West 20 98 97 22 East West 20 98 97 23 Eas! West 23 96 98 Table 4. Vehicle classification data (continued) WIM Site 24 Direction North South 25 East West 26 North South 27 North South 28 North South 29 North South 30 North South I Classification Site Used None None % Trucks in Outside Lane 100 100 I I YAVAPAI -* OCME-8 Figure 4. Automatic traffic recorder locations 18 Table 5. Automatic traffic recorder data WIM Site 1 Direction North South ATR Site Used 4 i Day of Week Tuesday Thursday Adjustment Factor .96 .99 2 East West 4 Wednesday Wednesday 1.02 .94 3 East West 4 Wednesday Wednesday 1.02 .94 5 East West 3 Tuesday Tuesday -97 .94 6 East West 3 Monday Monday .82 .99 8 East West 3 Monday Tuesday .82 .94 9 East West 3 Wednesday Wednesday 1.03 .06 10 East West 20 Wednesday Wednesday .96 .91 11 East West 20 Wednesday Wednesday .96 -91 12 East West 20 Thursday Thursday 1.00 .99 13 East West 5 Thursday Thursday .96 .97 15 East West 5 Wednesday Thursday .95 .97 18 East West 7 Wednesday Wednesday .97 .94 19 North South 27 Tuesday Tuesday .92 .91 20 East West 25 Wednesday Wednesday 1.07 .97 22 East West 2 Monday Monday .94 1.OO 23 East West 5 Wednesday Wednesday .95 .94 24 North South 5 Tuesday Tuesday .90 .87 Table 5. Automatic traffic recorder data (continued) WIM Site 25 26 North South Day of Week Thursday Thursday Tuesday Tuesday 27 North South Tuesday Wednesday 28 North South Tuesday Tuesday 29 North South North South Tuesday Thursday 30 Direction East West ATR Site Used 1 3 Tuesday Wednesday Adjustment Factor 1.11 1.14 1.12 1.14 .75 .78 .75 -77 .75 .83 .97 .96 Frequency adjustments by site and direction are presented in Table 6. Adjusted frequencies are represented as daily truck volumes on Figure 5. As was expected, the majority of trucks in the sample were class 9 (3S2). The percent of trucks in each vehicle class across all sites was as follows: Class 5 Percent 10.8 Table 6. Frequency adjustments by site and direction. WIM Site 1 Direction North South Raw 24 Hour 24 Hour Lane Day of Week Count Adjustment Adjustment Adjustment 475 --495 370 -411 4 15 East West 1068 1425 1961 2109 1601 2068 1703 East West 1654 1735 -- -- 1923 1958 1885 2082 5 East West 1587 1717 --- 2845 1929 1902 2052 6 East West 1445 1782 1784 2475 2176 2500 8 East West 1243 1736 ----- 1573 2 143 1918 2280 9 East West 2003 206 1 --- 2535 2544 2461 2650 10 East West 996 1534 1567 1888 1703 1888 1774 223 1 11 East West 2239 1952 -- 2434 2099 2535 2307 East West 1788 1743 -- 1943 1874 1943 1893 East West 2228 1865 -- 2684 2450 2796 2526 East West 2749 275 2391 33 12 2846 3486 2934 18 East West 1434 1235 --- 2313 1563 2389 1663 19 North South 503 520 --- 547 605 595 665 2 3 12 13 15 -- --2058 -- Table 6. Frequency adjustments by site and direction (continued) WIM Site 20 Direction East West Raw 24 Hour 24 Hour Count Adjustment -507 -49 1 Lane Day of Week Adjustment Adjustment 5 17 483 506 533 22 East West 543 653 --- 554 673 5 89 673 23 East West 636 815 --- 663 832 698 885 24 North South 795 97 1 --- -- -- 828 1116 East West 370 366 -- -- 41 1 411 370 36 1 26 North South 168 132 --- 187 148 167 130 27 North South 930 1213 --- 1069 1394 1425 1787 28 North Soutll 809 1258 --- 899 1353 1199 1757 29 North South 767 896 --- 872 1211 1163 1459 30 North South 28 1 307 --- 3 12 34 1 322 355 25 Other State Highways 183 Volume/Directlon Figure 5. Adjusted daily truck volumes by WIM site. 24 Weight Analysis Average gross weights and steering axle weights by vehicle classification for each site were computed; the results are included in Appendix E. The data were then aggregated, and the average gross truck weight and steering axle weight by vehicle class were computed. The results are presented in Table 7. As was expected, truck weight generally increases with vehicle classification, so that larger trucks have a higher average weight than smaller trucks. Generally, trucks using the Interstate routes were significantly heavier than those using State or U.S. routes, F(1,54811) =589.86, p < .0001 (See Appendix F for analysis tables). Trucks on Interstate routes averaged nearly 13,000 lbs. more than trucks on non-Interstate routes. Of particular interest for pavement design purposes is the average truck weight by route. Means by route are presented in descending order in Figure 6. It is immediately apparent that trucks on 1-17 and 1-40 weigh more on the average than trucks on other routes. This might be due to the type of commodity that the vehicles are transporting (e.g., manufactured goods vs. produce). Whatever the reason, this is an important finding which should be taken into consideration in the pavement design process. Table 7. Mean gross and steering axle weights by vehicle class. Gross weight Classification 5 6 7 8 9 10 11 12 13 Mean 19672.3278 34205.9404 38757.8384 43343.9743 59262.8950 70087.7175 60689.1964 68680.1964 67919.8421 Std. Dev. 23060.6713 37966.3588 40896.2133 43394.3005 22268.1645 49813.1917 32348.6569 38683.6016 50995.7378 Cases 5893 2079 464 6737 30795 1055 5689 1069 1032 For Entire Sample 52629.0442 32541.7158 54813 Mean Std. Dev. Cases 8395.0717 54813 Steering axle weight Classification For Entire Sample 7710.9068 Lbs. 1-17 1 1 1-40 I 1-10 SR 85 I 1-8 I L US89 Route Figure 6. Mean gross weight by route. I 1-19 US93 I US 60 SR 87 Equipment Analysis Because three of the Weighman machines used in this study were new (numbers 73, 74, and 80) and the other three were several years old (numbers 3, 5, and 14), it was suspected that there might be a difference in their operation. Unfortunately, the reliability tests which were conducted used machines of the same age. An analysis of gross weight by machine was thus considered imperative. Average gross truck weights by machine type for Interstate routes are presented in Figure 7. Observing this figure, it appears that there is a weight difference which can be attributed to machine age: new machines appear, on the average, to weigh "lighter" than old machines. Statistical analysis confirms that the average gross weights for the six machines differ significantly from each other (F(9,50705) = 136.01, p < .0001), as do the steering axle weights (F(9,50705) = 159.59, p c .0001). Because it has already been established that average truck weights differ significantly by route, a n analysis was conducted to rule out the possibility that the difference in weights by machine age can actually be attributed to the routes on which the machines were placed. When routes are held constant, a significant weight difference is still found for machine age, with older machines weighing heavier on the average than the newer machines (see Appendix F). 70,000 65,000 60,000 55,000 *1 -BOld 50,000 Lbs. New 45,000 40,000 35,000 30,008 I 1-10 I 1-17 I 1-19 Route Figure 7. Mean gross weight by machine type by route. 1 1-40 DISCUSSION Overall, WIM equipment appears to be a viable alternative to the loadometer for heavy vehicle data collection purposes: the sheer volume of data collected represents a significant improvement over the traditional loadometer approach. Although the weight variations (e.g., standard deviations) are much higher than desirable, it appears that the WIM systems on the average estimate gross truck weights within reasonable limits. However, some difficulties with the systems have been observed and should be mentioned. Perhaps the most notable of these is the equipment's erratic behavior. A successful installation in no way guaranteed proper system performance, as it was noticed that the system frequently functioned improperly or ceased to function altogether. (For details concerning problems on individual site installations, refer to the site notes in Appendix G.) Another identified problem was the tendency for temporary loops to be torn off of the pavement by heavy traffic. Use of a special adhesive on the pavement surface before taping the loops almost eliminated this difficulty. The adhesive primer also helped the system to remain affixed in rainy weather conditions. Still, greater success in installation overall was achieved with existing loops embedded in the pavement. By the end of the study, the WIM systems were definitely showing signs of wear. Mat surfaces became ostensibly dimpled, and their metal edges had broken from fatigue. SeveraI months after the data were collected, it was discovered that the cold solder joints connecting the oscillator wire to the plates inside the mat had disintegrated. It is not known what effect this had on data collection, as it is not possible to determine when the damage occurred. At times, the equipment ceased to function for no apparent reason. Frequently, troubleshooting was required on site, necessitating that a technician be present on location during all testing. Some problems are still a mystery. RECOMMENDATIONS It is clear that portable WIM systems can be valuable tools for extensive data collection efforts such as that required for pavement design. It is evident, however, that far more research and development is necessary before the particular portable WIM system used in this study can be put to practical use by non- technical personnel. Still, the advantages of using weigh in motion systems over traditional loadometer testing appear to outweigh the disadvantages. The use of WIM equipment has facilitated the collection of a large amount of data system-wide, which would not have been possible by any other means. Because data were collected over full 24 hour periods at most sites, they are most likely more representative of total truck traffic on the state highway system than loadometer data. It is recommended that the use of WIM equipment for truck data collection be further explored. The installation of permanent loops at selected sites would greatly facilitate future data collection efforts. Before beginning another large-scale data collection effort, however, it is recommended that the different portable WIM systems currently on the market be evaluated with an eye toward minimizing measurement error and equipment problems. REFERENCES (1) Basson, J.E.B, Visser, A.T., and Freerne, C.R. (1988). In-motion weighing of vehicles on heavily trafficked r o d . Transportation Research Board, Transportation Research Record 1200. 1-6. (2) Izadmehr, B. and Lee, C.L. (1988). Accuracy and tolerances of weigh-in-motiorzsystems. Transportation Research Board, Transportation Research Record 1123, 127-135. (3) Broussard, D.T. (1988). Weigh-in-motionfor planning applications in Louisiana. Federal Highway Administration, Report No. FHWA/LA-87/196. (4) Davies, P. and Sommerville, F. (1988). Calibration and accuracy testing of weigh-in-motion systems. Transportation Research Board, Transportation Research Record 1123, 122- 126. APPENDICES APPENDIX A Vehicle Classification Scheme Vehicle Classification Records 1. General Comments Vehicle classification data collected at truck weigh sites are necessary to expand the truck weight information to the distribution of the various types of trucks in the traffic stream. The FHWA vehicle classification categories are discussed in Section 4 and the definitions are repeated here as a reference for the vehicle classification record format immediately following them. Tywe Name and Description 1. Motorc~cles (Optional) -- All two- or three-wheeled motorized vehicles. Typical vehicles in this category have saddle-type seats and are steered by handle bars rather than a wheel. This category includes motorcycles, motor scooters, mopeds, motor-powered bicycles, and three-wheel motorcycles. This vehicle type may be reported at the option of the State. 2. Passenser Cars -- All sedans, coupes, and station wagons manufactured primarily for the purpose of carrying passengers and including those passenger cars pulling recreational or other light trailers. 3. 4. Other Two-Axle. Four-Tire Sinale Unit Vehicles -- All twoaxle, four-tire vehicles, other than passenger cars. Included in this classification are pickups, panels, vans and other vehicles such as campers, motor homes, ambulances, hearses, and carryalls. Other two-axle, four-tire single unit vehicles pulling recreational or other light trailers are included in this classification. Buses -- All vehicles manufactured as traditional passengercarrying buses with two axles and six tires or three or more axles. This category includes only traditional buses (including school buses) functioning as passenger-carrying vehicles. All two-axle, four-tire minibuses should be classified as other two-axle, four-tire single unit vehicles. Modified buses should be considered to be a truck and be appropriately classified. NOTE: a. In reporting information on trucks the following criteria should be used: Truck tractor units traveling without a trailer will be considered single unit trucks. 5. 6. b. A truck tractor unit pulling other such units in a "saddle mount" configuration will be considered as one single unit truck and will be defined only by the axles on the pulling unit. c. Vehicles shall be defined by the number of axles in contact with the roadway. Therefore, 81floating"axles are counted only when in the down position. d. The term trailers. I1trailerl1 includes both semi- and full Two-Axle, Six-Tire, Sinqle Unit Trucks -- All vehicles on a single fram including trucks, camping and recreational vehicles, motor homes, etc., having two axles and dual rear wheels. Three-Axle Sinsle Unit Trucks -- All vehicles on a single frame including trucks, camping and recreational vehicles, motor homes, etc., having three axles. 7. Four or More Axle Sinqle Unit Trucks -- All trucks on a single frame with four or more axles. 8. Four or Less Axle Sinale Trailer Trucks -- All vehicles with four or less axles consisting of two units, one of which is a tractor or straight truck power unit. 9. 10. 11. 12. Five-Axle Sinale Trailer Trucks -- A five-axle vehicles consisting of two units, one of which is a tractor or straight truck power unit. Six or More Axle Sinqle Trailer Trucks -- All vehicles with six or more axles consisting of two units, one of which is a tractor or straight truck power unit. Five or Less Axle Multi-Trailer Trucks -- All vehicles with five or less axles consisting of three or more units, one of which is a tractor or straight truck power unit. Six-Axie Multi-Trailer Trucks -- All six-axle vehicles consisting of three or more units, one of which is a tractor or straight truck power unit. 13. -- Seven o r More Axle M u l t i - T r a i l e r T r u c k s A l l v e h i c l e s with s e v e n o r more a x l e s c o n s i s t i n g of t h r e e o r more u n i t s , one of which i s a t r a c t o r o r s t r a i g h t t r u c k power u n i t . DF&F\X PTXQN blot 01.cyola:i Pasaonger Curs* 0 l . h ~2 A x I c , 4 10' < 2 A%l.Ef 5 AXlXa 13' 15' < < A 1 - A 2 . < 23' A 1 4 2 < 2q' AND A 4 - A 5 4 ANY NOT C1,ASSJFIED EIJEWI4EHE 10' l'lro, 5 4 or loaa Axle SLnglo l'ral 1et' TrucI{~ 8 I ; Tr'al lfsr Trucks I , I 7 or' Ilora Axle MultiTx*alieta 'rruf:k,:~ * 111~:l > 3 AXCUr A243 4 hY.Itl<% h2-A3 4 A XI A243 < 3.5' 1U' > 5' <#* 3.5' G AX1.E: 3.5' hNDA3-A4 5 ' AND A3.-A4 > 3.5' i 10' < A.7-A4 C 5' ANY NOT CLASSIFIED EI.vSEWHEHE > < 18' 13' 13' ANI) 10' < A2-A3 < 1n' 13' AND h 3 - A 4 < 3 . 5 ' 15' AND h4-AS < 3 . 5 ' < h4-A5 <-0' AND A2-A3 < 6 . 1 ' ANY NOT CLASSIFIED BI,SCWlIERE 5 AXLE1 5 AXLI:: 6 A;Y[,Et 5 or luau Axlo Multi- < Al-A?,< hl-A2 < A1-42 < Al-A2 < 10' 10' ' S l . f ~ g l eUnit 'I'ruckan 120" 120" AN0 ANI) 10' < A2..h3 120" AND A3-A4 < 3 . 5 ' < < < Tire, S l n g l u Unit Vul)iclsen s7 Axlo, 6 < < hi-A2 Al-.A2 Al-A2 il 5 AXLE: A2-A3 13 7 AXLEX ANY 7 AXLE VEHICLE ANY VEHICLE NOT CLASSIPIED ELSF:Wlll3HE 6' , udes vc.1) l clt>sp u l l 118 r'ecrso~ionalor otller 1Igl~ttrnl lttrs. APPENDIX B WIM Data Collection Sites WIM Data Collection Sites WIM Site 1 Date Route North South East West East West East West East West East West East West East West East West East West East West lO/4/88 10/6/88 11/2/88 11/2/88 5131/89 5/31/89 10/25/88 10125188 9/12/88 9/12/88 11/7/88 11/8/88 5/10/89 5/10/89 3/9/89 3/9/89 2/1/89 5/17/89 7/14/88 7/14/88 4/13/89 4/13/89 East West East West North South 3/16/89 12/1/88 4/26/89 4/26/89 4/18/89 4/18/89 20 East West 5/3/89 5/3/89 22 East West East West 5/1/89 511189 9/28/88 9/28/88 North South 9/27/88 9/27/88 US 93 US 93 1-40 1-40 1-40 1-40 1-40 1-40 1-40 1-40 1-40 1-40 1-40 1-40 1-10 1-10 1-10 1-10 i-10 1-10 1-10 I- 10 I- 10 I- 10 1-10 I- 10 I-19 1-19 1-8 1-8 1-8 1-8 1-8 1-8 SR 85 SR 85 2 3 5 6 8 9 10 11 12 13 15 18 19 23 24 Direction "KiIorneter post Milepost 035.2 047.5 009.0 009.0 056.0 056.0 179.7 179.7 319.5 3 19.5 343.0 343.0 014.0 014.0 04 1.O 04 1.O 129.2 129.2 180.0 180.0 239.5 239.5 360.0 360.0 046.0" 046.0' 105.0 105.0 134.5 134.5 149.0 149.0 Machine No. WIM Site 25 26 27 28 29 30 Direction East West North South North South North South North South North South Date Route Milepost 2116/89 2/16/89 2/28/89 2/28/89 11/29/88 5/24/89 10/18/88 10/18/88 8/23/88 10/27/88 9/13/88 9/14/88 US 60 US 60 SR 87 SR 87 1-17 I- 17 1-17 1-17 1-17 1-17 US 89 US 89 206.0 206.0 200.2 199.1 233.4 242.0 273.0 269.5 335.0 335.0 434.2 434.2 Machine No. 73 74 73 74 80 74 74 14 14 3 14 14 APPENDIX C Frequency Data for Individual Sites 1 NORTH Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE IfiOillllEill[l Y ]I( #311113#3[ iiii#t#iiiii#ifiii~iHi]Iii##iMi #I ]1]11111[# ]I #Ell \-"""" 1 t 80 t 160 t 240 Histogram Frequency V a l i d Cases 475 --------- I t 320 400 """" " ' ""'' "--"'- Missing Cases 0 1 SOUTH Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 liiii%Hiii#fi##i ill# la# Ii#ii%iiil#fltiiii ~ i % # i ~ % i i ~ i P l i i i i i ~ I % # l # ~ i % l i i I # I I i 1 ] B ( I ~ I E ~ ~ la## iiliii i 111 \---------t --------- f ---------t ---------t --------- I 0 40 120 80 Histogram Frequency Valid Cases 370 Missing Cases 0 160 200 2 EAST Valid Value Frequency Percent Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 Xll[#lil# 1 tiii1 liii1iii1iP11ifi1iiiEi1[ifiP[iiI1I1]8[~]8[li[iii~~ 1 iiiif1iiii 1 1 \---------+--------0 160 ---------t ---------t --------- 1 t 320 480 640 800 Histogram F r e q u e n c y Valid C a s e s 1068 Missing C a s e s 0 2 WEST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 iitriirif iiiii#i Hi# i#f~i~iiiiiiiii~iiliiii111#ifii#if#If1D[~IIf~~ ifi#Hii#iii#~iiiiii1[iXIifiiI IIiiii ftiliili%#iii# i#i i#li#R \--------t ---------t ---------t --------- f --------- I 0 120 360 240 Histogram Frequency V a l i d Cases 142 5 Missing Cases 0 480 6 00 3 EAST Value 5 6 7 8 9 10 11 12 13 Frequency Percent 98 24 10 14 3 1068 33 202 31 45 5.9 1.5 .6 8.6 64.6 2.0 12.2 1.9 2.7 5.9 1.5 .6 8.6 64.6 2.0 12.2 1.9 2.7 1654 VALUE 1654 5.9 7.4 8.0 16.6 81.2 83.2 95.4 97.3 100.0 100.0 Histogram Frequency Valid Cases Cum Percent ------- ------- ------- TOTAL COUNT Valid Percent Missing Cases 0 100.0 3 WEST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE ##IO[#Y(I##l# f #I# I I##Il#~til#I#IiIi#fi ii#iiI~#iiP~tiii#i####IIit1[ilIY(#iIlitIItYi I Iii#ill#Il I # + \---------t ---------t ---------t --------- --------0 Valid Cases 1735 200 400 600 Histogram Frequency Missing C a s e s 0 800 1000 5 EAST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 1587 Missing Cases 0 5 WEST Valid Value Frequency Percent Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 1iW[#i 1i 1iti111i 1i11ii~i1i11#1i11#i1#iI#1#ii1i##1X]0[i#]0[#P#~B~~~BE 1 iiiiiii 1 1 \--------- t ---------t ---------t ---------t --------- 1 0 240 480 720 H i s t o g r a m Frequency Valid C a s e s 1717 Missing C a s e s 0 960 1200 6 EAST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 ###### ##I ##I### ######iiii#Kil####~##]I[###~#I1[#]I[#i#]I[]DIH#ii#~~%% if###### #Ill[ ### \--------0 +---------t ---------t ---------t --------- I 2 00 400 600 Histogram Frequency Valid Cases 1445 Missing Cases 0 800 1000 6 WEST Value Frequency Percent Val i d Percent Cum Percent TOTAL COUNT VALUE Hi### ffiIi#~#i#R#ii#fii##Ii#Ii##I[IIi]I[#]I[iI]DI#~~#%~~~%B I ###I]I[#]11#1[1I I I \ 1 V a l i d Cases 17 8 2 ---------t --------- t ---------t ---------t --------- I 240 480 720 Histogram Frequency Missing Cases 0 960 120 0 8 EAST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 ##I1 # i1i flii~iiiillii~iii#i11[##iI[iii~i1[IPili[P]II~I~ # i1iiiiliii 1[ l \--------- t 0 ---------t --------- t ---------t --------- I 200 400 600 Histogram F r e q u e n c y Valid Cases 1243 Missing Cases 0 800 1000 8 WEST Value Frequency Percent Valid Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 1736 Missing C a s e s 0 Cum Percent 9 EAST Value Percent Frequency Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 ###I# 11[ #### I#####ii####li#if#i~l####]I[#f####B]DI]DIBPII~~~%~E~~ ###a#### # 0 Valid Cases +---------t ---------t ---------t \--------- 2003 900 600 Histogram F r e q u e n c y 300 Missing C a s e s 0 1 "--'-"' 1200 1500 9 WEST Value Frequency Percent Valid Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 2061 Missing Cases 0 Cum Percent 10 EAST Value Frequency Percent Valid Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 996 Missing Cases 0 Cum Percent 10 WEST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE ##BE## #I i iiiiil I ~ i i i i i f f i # i i # i f i Y l t # ] I I l t i i # # I I l i # i I # I i I i # ~ % ~ I### Iill[a[i#Iii# HBW( #I## \--------- t ---------t --------- t --------- t --------- I 0 200 400 600 Histogram Frequency Valid Cases 1534 M i s s i n g Cases 0 800 1000 11 EAST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 311lH11#11111 311 3 3111111iii 311111~111~11111111111111111M11lHHiiIII[]s[II(MII#11111111~II[I]8[~~%E 3 31111111111i111111 311s 3 I.........I.........I.........I.........I......... 0 300 600 900 Histogram Frequency Valid Cases 2239 Missing C a s e s 0 1200 1 50 11 WEST Value Frequency Percent Valid Percent 5 6 7 8 9 10 11 12 13 TOTAL COUNT VALUE Histogram Frequency V a l i d Cases 1952 Missing Cases 0 Cum Percent 12 EAST Value Frequency Percent Val i d Percent Cum Percent 5 6 7 8 9 10 11 12 13 TOTAL COUNT VALUE \--------- t --------- t ---------t --------- t --------- I I 0 240 720 480 Histogram Frequency Valid Cases 1788 Missing Cases 0 960 12 0 0 12 WEST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE Ii##i##H##ii# #PX1#IYIIiIII# 111111 i%i#li#####i# 111111~#i~#ii##i111i111i##111X1#111111111###111111111#1111111Ir111I111Ir~ ]1(111#1%]1[# r ~ i ~ ~ r ~ ~ ~ #Iff# #lIli[YlO[iiI \---------t ---------t --------- t --------- t --------- 1 0 V a l i d Cases 1 7 43 160 320 480 Histogram Frequency Missing C a s e s 0 640 800 13 EAST Value Frequency Percent Valid Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 2228 Missing C a s e s 0 Cum Percent 1 3 WEST Value Frequency Percent Val id Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 1865 Missing Cases 0 Cum Percent 15 EAST Value Frequency Percent Valid Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 2749 Missing Cases 0 Cum Percent 15 WEST Value Frequency Val id Percent Percent Cum Percent TOTAL COUNT VALUE 52 16 1 62 120 2 19 3 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 PIPlf~##H###1 ##ill i ~ i ~ i i i i f i f i ~ i i i ##i##Y#i#11i#ii1iii1#~i3I#~#1~# i i131[1311 1 \---------t 0 40 ---------+---------t ---------f --------- 1 80 120 Histogram Frequency Valid Cases 275 Missing Cases 0 160 200 1 8 EAST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE I \--------t --------- t ---------f ---------t --------- 1 0 Valid Cases 1434 240 480 720 Histogram Frequency Missing C a s e s 0 960 1200 18 WEST Value Frequency Percent Valid Percent Cum Percent 5 6 7 8 9 10 11 12 13 TOTAL COUNT VALUE I: I## \--------t ---------t ---------t --------- t --------- 1 0 200 400 600 Histogram Frequency Valid Cases 1235 Missing Cases 0 800 1000 19 NORTH Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE I rcrcr \---------+---------+-------0 Valid Cases 503 +---------t --------- 1 160 240 Histogram Frequency 80 Missing Cases 0 320 4 00 19 SOUTH Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE I \---------+--------0 80 i----------t --------- t --------- 1 160 240 Histogram Frequency Valid Cases 520 Missing Cases 0 320 400 20 EAST Value Frequency Percent Valid Percent 5 6 7 8 9 10 11 12 TOTAL COUNT VALUE Histogram Frequency Valid Cases 507 Missing Cases 0 Cum Percent 20 WEST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 Iflliil# i# iiiiiiii iifiiiifiiiliiiiiiii]tiiIIiiII[i]i[I]s[IP181 i Eriiirii E li[ \---------t ---------t ---------t --------- f -----0 80 240 160 Histogram Frequency V a l i d Cases Missing Cases 0 320 22 EAST Value Frequency Percent Valid Percent Cum Percent 5 6 7 8 9 10 11 12 13 TOTAL COUNT VALUE I \--------t ---------t ---------t --------0 80 160 240 Histogram Frequency Valid Cases 543 Missing Cases 0 +--------- 1 320 400 22 WEST Value Frequency Percent Valid Cum Percent Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 653 Missing Cases 0 23 EAST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 33 7 1 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 44 4 52 18 40 17 24 iii i ii## i#i#ilIIi~##ifiiiiii#ii#IIIi]I31[w[~IIiiI~I~iiI E l i # i i 1i \---------t ---------t --------- 'r --------- t --------0 100 200 300 Histogram Frequency V a l i d Cases 636 Missing Cases 0 400 1 500 23 WEST Value Frequency Percent V a l id Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 31]13111[ i# ##Elf### 11ii31#313131#313131#fi11[31~11[i311[31111#]81II31I##31#I##lg##lg~~%~~~~%% 31 31313131 # 11 \---------+--------0 Valid Cases 815 +---------t ---------t 360 240 Histogram F r e q u e n c y 120 Missing C a s e s 0 480 me------- 1 600 24 NORTH Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE i11iiiili 1111 I #####Hi## t11i~iiY#Ii##l##iiii#IlIIii]I(#]D[iHi#iIIII]81#I~]I( a11 11111#11[1[1# ##I I # +---------t ----------t---------t --------- 1 \--------0 Valid Cases 745 300 100 200 Histogram Frequency Missing Cases 0 400 500 2 4 SOUTH Valid Value Frequency Percent Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 iiiiili I### i iS1[#1[ i s i i i i i i r i i i i i i i i i I i i a i i i ~ ~ 1 [ B ~ i i ~ 1 o [ i t g 1 o [ a i a ~ a #SiifiI Iri #it### \---------t --------- t ---------t --------0 Valid Cases 971 120 240 360 Histogram Frequency Missing Cases 0 + 480 me------- I 600 25 EAST Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 ################################EB# asiirii iiiliiliiili ##l###i~~#il#i###~~###########I~i#)8[ # ### l \---------t ---------t --------- t --------- t --------- 1 0 Valid C a s e s 370 40 80 120 Histogram Frequency Missing C a s e s 0 160 200 25 WEST Value Frequency Percent Val i d Percent Cum Percent 5 6 7 8 9 10 11 12 13 TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 # i ~ i f ~ I i # f ~ I i i i i i ~ i i # I i # if###### 1 fi#iii#lfi####iiII iflii#ii###1iiii##iiII##1(##I1(1(#i#~ ###I# I# I II \---------t 0 40 ---------t ---------t --------- t --------- I 80 120 Histogram Frequency Valid Cases 366 Missing Cases 0 160 200 2 6 NORTH Frequency Value Percent Valid Percent Cum Percent TOTAL COUNT VALUE i i i f i r i i ~ i i i r i r r i i i i ~ ~ i i ~ i ~ ~ i i i i a ~ a i g i ~ i iiii~iiiiiiiiifiiiiifii]81liiiYIiii ]IIT liiiiiiiiiil ii iifiiiiiiii \--------- t ---------t ---------t ---------t --------- I 0 Valid Cases 168 30 20 Histogram Frequency 10 Missing C a s e s 0 40 50 26 SOUTH Value Frequency Percent Val id Percent Cum Percent 5 6 7 8 9 10 11 12 TOTAL COUNT VALUE lli11l~IIYIll11lilflill111[i11i1Eill1111#11fB 1YH I11 i11ii#i##ii11l#i11 ~ ~ i ~ ~ i i r ~ i r r ~ ~ i ~ i i i ~ ~ ~ ~ ] ~ Ill# riYW(#lr b 1 Valid Cases i --------t --------- t ---------t ---------t --------- 1 132 36 24 Histogram Frequency 12 Missing Cases 0 48 60 27 NORTH Value Frequency Percent Valid Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 930 Missing Cases 0 Cum Percent 27 SOUTH Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 i i i i # i i i i i i i frriiiiriiii #fig iiiilititiiiii i i # i i ~ i l i i i i i f i f i i ~ I I [ ~ l l I I i I I i I i I i i I i # I I I g % i ~ I g ~ % ~ % ~ 1[113[131( i i I i f i i # i # i i liii E i l i i f i # i i i i i \---------t --------- t --------- t ---------t --------0 2 00 300 Histogram Frequency 100 400 I 500 2 8 NORTH Value Frequency Percent Valid Percent TOTAL COUNT VALUE Histogram Frequency V a l i d Cases 809 M i s s i n g Cases 0 Cum Percent 2 8 SOUTH Value Frequency Percent Val id Percent TOTAL COUNT VALUE Histogram Frequency Valid Cases 1258 Missing Cases 0 Cum Percent 2 9 NORTH Value Frequency Percent Valid Percent Inn, n TOTAL COUNT Cum Percent VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13 .OO i i i i i f f i i i i i # i i i i # i i iiiii i i i i # i i i i i i i f i r r i i i r i i r i i i i i i i # i i i i i i i i ~ a g i ~ ~ g i i g 1 8 o I I ~ ~ ~ ~ ~ i i i r i i g i i i i i 1[ i \---------t 0 ---------t ---------t 80 240 160 Histogram F r e q u e n c y V a l i d Cases 767 Missing Cases 0 --------- I t 320 400 29 SOUTH Value Frequency Percent Valid Percent Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 iiiiiiiNB##iiii iiiiiir i R i i i i i i iiiiiiiiii#ii~iii~iiiNiiiii1(i#NB]I]8[91~]8[II]I[~~B~ i i i i Y i i i i i i i ]I iii \---------t ---------t --------- t ---------t --------- I 0 Valid C a s e s 896 100 200 3 00 Histogram Frequency Missing C a s e s 0 400 5 00 30 NORTH Value Valid Percent Percent Frequency Cum Percent TOTAL COUNT VALUE 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 iifiiiiii##iliii #I11 1 liiiiiilf #Piiiifff1Mi#~#i#il1~1l11[]I[#f111 la ##iliI#i i1 +---------t ---------f ---------t --------- 1 \--------0 40 80 120 Histogram Frequency Valid Cases 281 Missing Cases 0 160 200 30 SOUTH Value Frequency Percent Valid Percent cum Percent TOTAL COUNT VALUE f t i P I I I f i i f i i i i i #is# i iiiiii#fiii iiiirr~iriiiiiiiriiiiiiii~iii 1[1 31PIiPIIPII ]w PI #iiPIiPI# \---------t --------- t --------- t --------- t --------- I 0 40 120 80 Histogram Frequency Valid Cases 3 07 Missing Cases 0 160 200 APPENDIX D Automatic Traffic Recorder Data ATR 1 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean Std D e v Cases Mean Std Dev Cases For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases 73 2 = DIR 2 Summaries of By levels of Variable ADT DAY Value Label For Entire Population 1 2 3 4 5 6 7 DAY DAY DAY DAY DAY DAY DAY Total Cases = 73 2 ATR 2 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean Std D e v Cases Mean Std Dev Cases For Entire Population DAY DAY DAY DAY DAY DAY DAY 1 2 3 4 5 6 7 Total Cases = 732 DIR 2 Summaries of By levels of Variable ADT DAY Value For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = Label ATR 4 DIR 1 Summaries of By l e v e l s of Variable ADT DAY Value Label Std D e v Cases For Entire Population 594.8931 732 DAY DAY DAY DAY DAY DAY DAY 495.5859 498.7150 487.2383 472.1343 498.6813 675.6397 572.0682 104 104 104 104 104 106 106 Std D e v Cases Total C a s e s = Mean 732 DIR 2 Summaries of By levels of Variable ADT DAY Value Label For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 Mean ATR 5 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 DIR 2 Summaries of By levels of Variable ADT DAY Value Label For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 ATR 7 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases 1 2 3 4 5 6 7 = 732 DIR 2 Summaries of By levels of Variable ADT DAY Value Label For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 ATR 9 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 DIR 2 Summaries of By levels of Variable ADT DAY Value Label For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 1 2 3 4 5 6 7 732 ATR 1 2 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean S t d Dev Cases Mean Std Dev Cases For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 DIR 2 summaries of By levels of Variable ADT DAY Value Label For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 1 2 3 4 5 6 7 732 ATR 14 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean Std Dev Cases Mean Std Dev Cases F o r Entire Population DAY DAY DAY DAY DAY DAY DAY 732 Total Cases = DIR 2 Summaries of By levels of Variable ADT DAY Value Label For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 1 2 3 4 5 6 7 732 ATR 20 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 DIR 2 Summaries of By levels of Variable ADT DAY Value Label For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 ATR 25 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 DIR 2 Summaries of By levels of Variable ADT DAY Value Label For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 7 32 ATR 27 DIR 1 Summaries of By levels of Variable ADT DAY Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 DIR 2 Summaries of By levels of Variable ADT DAY Value Label For Entire ~opulation DAY DAY DAY DAY DAY DAY DAY Total Cases = 732 APPENDIX E Descriptive Statistics for Individual Sites 1 NORTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS *T 'a .-.m CILIC)oa CLASS CLASS Total Cases = Summaries of By levels of Variable 475 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 475 Mean Std Dev Cases 1 SOUTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 5 6 7 8 9 10 11 12 13 Total Cases = Summaries of By levels of Variable 370 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 370 2 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1068 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1068 Mean Std Dev Cases 2 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases Summaries of By levels of Variable 5 6 7 8 9 10 11 12 13 = 1425 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1425 Mean Std Dev Cases 3 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1654 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1654 Mean Std Dev Cases 3 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1735 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1735 5 EAST Summaries of By levels of Variable GROSS CLASS Value Label For Entire Population Mean Std Dev Cases 88817.8677 47745.7358 CLASS CLASS CLASS CLASS CLASS CLASS CLASS A- - -- LU33 CLASS Total Cases = Sumn~ariesof By levels of Variable 1587 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1587 Mean Std Dev Cases 5 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CMSS CLASS 1717 Total Cases = Summaries of By levels of Variable FFWTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 5 6 7 8 9 10 11 12 13 1717 Mean Std Dev Cases 6 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 5 6 7 8 9 10 11 12 13 Total Cases = Summaries of By levels of Variable 1445 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1445 Mean Std Dev Cases 6 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS 10 11 CLASS 12 CLASS 13 5 6 7 8 9 Total Cases = Summaries of By levels of Variable 1782 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1782 Mean Std Dev Cases 8 EAST Summaries of By levels of Variable GROSS CLASS Label Value Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 5 6 7 8 9 10 11 12 13 Total Cases = Summaries of By levels of Variable 1243 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1243 Mean Std Dev Cases 8 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1736 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1736 9 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire ~opulation CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 2003 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 2 003 9 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean S t d Dev Cases Mean S t d Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 5 6 7 8 9 10 11 12 13 Total Cases = Summaries of By levels of Variable 2061 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 2061 10 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 996 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 996 10 WEST Summaries of By levels of Variable GROSS CLASS Label Value Mean Std Dev Cases Mean Std ljev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS mr ...-.- LU33 CLASS Total Cases Summaries of By levels of Variable = 1534 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1534 11 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population 2239 CLASS CLASS CLASS CLASS CLASS CLASS CLASS 201 20 13 19 1 1471 13 260 63 7 CLASS CLASS 2239 Total Cases = Summaries of By levels of Variable FRNTAXL CLASS Value Label Mean Std Dev Cases For Entire Population 2239 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 201 20 13 191 1471 13 260 63 7 Total Cases = 5 6 7 8 9 10 11 12 13 2239 11 WEST Summaries of By levels of Variable GROSS CLASS Value Label For Entire Population Mean Std Dev Cases 51305.0348 24468.9129 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1952 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1952 Mean Std Dev Cases 12 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1788 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1788 12 WEST Summaries of By levels of Variable GROSS CLASS Value Llabel For Entire Population Mean Std Dev Cases 36591.8692 24673.7578 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1743 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1743 Mean Std Dev Cases 13 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 2228 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 2228 13 WEST Summaries of By levels of Variable GROSS CLASS Value Label For ~ n t i r ePopulation Mean Std Dev Cases 53091.7962 28509.6998 CLASS CLASS CL9SS CLASS CLASS CLASS CLASS cmss CLASS Total Cases = Summaries of By levels of Variable 1865 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1865 Mean 7103.2708 Std Dev Cases 15 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 2749 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 5 6 7 8 9 10 11 12 13 2749 30 NORTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 281 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 5 6 7 8 9 10 11 12 13 281 30 SOUTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable FRNTAXL CLASS Value For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Label 15 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 275 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 275 18 EAST Summaries of By levels of Variable GROSS CLASS Label Value For Entire Population Mean Std Dev Cases 57083.3536 23910.4519 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1434 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS 5 6 7 8 9 10 CLASS CLASS CLASS 11 12 13 Total Cases = 14 34 Mean Std Dev Cases 18 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1235 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1235 19 NORTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CIASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 503 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 503 19 SOUTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 52 0 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 5 6 8 9 10 11 12 13 520 20 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 5 6 7 8 9 10 11 12 507 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 507 Mean Std Dev Cases 20 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases Summaries of By levels of Variable 5 6 7 8 9 10 11 12 13 = 491 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 491 22 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 543 FRNTAXL CLASS Value Label Mean Std Dev Cases For Entire Population 54 3 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 68 9 1 78 296 3 78 Total Cases = 7 3 543 22 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 5 6 7 8 9 10 11 12 13 Total Cases = Summaries of By levels of Variable 653 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 653 23 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 636 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 5 6 7 8 9 10 11 12 13 636 23 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 815 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 8 15 24 Summaries of By levels of Variable NORTH GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 745 24 SOUTH Summaries of By levels of Variable GROSS CUSS Label Value For Entire Population Mean Std Dev Cases 46357.6931 23119.0244 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 971 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 5 6 7 8 9 10 11 12 13 971 Mean Std Dev Cases 25 EAST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population 370 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 139 5 6 7 8 9 10 11 12 13 Total Cases = Summaries of By levels of Variable FRNTAXL CLASS Value Label Mean Std Dev Cases For Entire Population 370 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 139 Total Cases = 5 6 -? 8 9 10 11 12 13 25 WEST Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 366 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 366 26 NORTH Summaries of By levels of Variable GROSS CTASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 5 6 8 9 10 11 12 13 Total Cases = Summaries of By levels of Variable 168 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CUSS CLASS Total Cases = 2 6 SOUTH summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 132 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 132 27 NORTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS 5 6 7 8 9 10 11 12 13 Total Cases = Summaries of By levels of Variable 930 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 930 27 SOUTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 1213 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1213 28 NORTH Summaries of By levels of Variable GROSS CLASS Value Label For Entire Population Mean Std Dev Cases 58234.8059 38130.8333 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 809 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 809 Mean Std Dev 9798.4574 12479.1279 Cases 28 SOUTH Summaries of GROSS CLASS By levels of Variable Label Value For Entire Population Mean Std Dev Cases 91643.2560 61267.8925 CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = FRNTAXL Summaries of By levels of Variable 1258 CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 1258 Mean Std Dev 25441.8983 20037.5524 Cases 29 NORTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 767 29 SOUTH Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of By levels of Variable 896 FRNTAXL CLASS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 896 APPENDIX F Statistical Analysis Tables Summaries of By levels of Variable GROSS CLASS Value Label Mean Std Dev Cases For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = Summaries of BY levels of Variable 54813 ST AXLE CGSS Value Label For Entire Population CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS CLASS Total Cases = 54813 Mean Std Dev Cases Summaries of By levels of Variable GROSS ROUTE Value Label Mean Std Dev Cases For Entire Population ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE Total Cases = Summaries of BY levels of Variable 54813 ST AXLE RO~TE Value Label For Entire Population ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE ROUTE Total Cases = 54813 Mean Std Dev Cases MANOVA BY SITE 54813 0 0 24 c a s e s accepted. c a s e s r e j e c t e d because o f out-of-range f a c t o r v a l u e s . c a s e s r e j e c t e d because o f m i s s i n g d a t a . non-empty c e l l s . 1 d e s i g n w i l l be processed. ---------C e l l Means and Standard Deviations Variable GROSS FACTOR CODE Mean .. SITE 1 SITE 2 SITE 3 SITE 25 SITE 5 SITE 6 SITE 26 SITE 8 SITE 9 10 SITE SITE 11 SITE 12 SITE 13 SITE 27 SITE 15 SITE 28 SITE 29 SITE 18 SITE 19 SITE 20 SITE 30 SITE 22 SITE 23 SITE 24 For e n t i r e sample S t d . Dev. .. Variable ST AXLE FACTOR CODE SITE SITE SITE SITE SITE SITE SITE SITE SITE SITE SITE SITE SITE SITE Std. Dev. Mean N 1 2 3 25 5 6 26 8 9 10 11 12 13 27 i5 28 17 18 19 20 30 22 23 24 s I'I'E SITE SITE SITE SITE SITE SITE SITE SITE SITE For entire sample - - - - - - - - - - * * ANALYSIS OF VARIANCE -- DESIGN 1 * * .. EFFECT SITE Multivariate Tests of Significance (S = 2, M Test Name Pillais Hotellings Wilks Roys Value .I6917 .I9030 .83588 .I3042 = 10 Approx. F Hypoth. DF 220.11627 226.64780 223.38004 46.00 46.00 46.00 , N = 27393 ) Error DF Sig. of F 109578.00 109574.00 109576.00 .OOO .OOO .OOO - - - - - - - - - Univariate F-tests with (23,54789) D. F. Variable Hypoth. SS Error SS Hypoth. MS Error MS GROSS ST-AXLE 4.59543+12 5.3448E+13 1.9980E+11 975532761 4.93223+11 3.36983+12 2.14443+10 61504668.6 F Sig. o 204.81251 .OO 348.66109 .OO MANOVA ON ROUTE TYPE 54813 0 0 2 cases accepted. cases rejected because of out-of-range factor values. cases rejected because of missing data. non-empty cells. 1 design will be processed. ---------Cell Means and Standard Deviations Variable GROSS FACTOR CODE .. RTTYPE INTERSTA RTTY PE NON- INTE For entire sample Mean 53582.270 40801.159 52629.044 Std. Dev. 32757.547 27075.729 32541.716 50725 4088 54813 ---------- .. Variable ST-AXLE FACTOR CODE Mean N Std. Dev. RTTY PE INTERSTA RTTYPE NON-INTE For entire sample ---------- * * ANALYSIS OF VARIANCE -- DESIGN 1 * * .. EFFECT RTTYPE Multivariate Tests of Significance (S = 1, M = 0, N = 27404 ) Test Name Pillais Hotellings Wilks Roys Value .01079 .01091 .98921 .01079 Approx. F Hypoth. DF Error DF Sig. of F 298.98351 298.98351 298.98351 54810.00 54810.00 54810.00 .OOO ,000 ,000 2.00 2.00 2.00 ---------Univariate F-tests with (1,54811) D. F. Error SS Hypoth. MS Variable Hypoth. SS Error MS GROSS ST-AXLE 6.1800E+ll 5.74263+13 6.1800E+ll 1047707528 1.6016E+10 3.84703+12 1.6016E+10 70186303.3 F Sig. of F 589.85669 228.19789 .000 .000 MANOVA BY ROUTE (INTERSTATE ONLY) 50725 0 0 5 cases accepted. cases rejected because of out-of-range factor values. cases rejected because of missing data. non-empty cells. 1 design will be processed. Cell Means and Standard Deviations Variable GROSS FACTOR CODE .. ROUTE I ROUTE I ROUTE I ROUTE I ROUTE I For entire sample Mean Std. Dev. Mean Std. Dev. 8 10 17 19 40 ---------- .. Variable ST-AXLE FACTOR ROUTE I ROUTE I ROUTE 1 ROUTE 1 ROUTE 1 For entire sample CODE 8 10 17 19 40 ---------- * * ANALYSIS OF N VARIANCE -- DESIGN 1 * * .. EFFECT ROUTE Multivariate Tests of Significance (S = 2, M = 1/2, N = 25358 1/2) Test Name Value Pillais Hotellings Wilks Roy s .07581 .08053 .92486 .06566 Approx. F Hypoth. DF 499.57738 510.53107 505.05320 8.00 8.00 8.00 Error DF Sig. of F 101440.00 101436.00 101438.00 .OOO .OOO .OOO ---------Univariate F-tests with (4,50720) D. F. Variable Hypoth. SS GROSS 1.76023+12 5.2670E+13 4.4005E+11 1038437549 2.47493+11 3.57613+12 6.18743+10 70506630.3 ST-AXLE Error SS Hypoth. MS Error MS F Sig. of F 423.75805 877.55837 .000 ,000 MANOVA BY MACHINE cases accepted. cases rejected because of out-of-range factor values. cases rejected because of missing data. non-empty cells. 47140 7673 0 6 1 design will be processed. Cell Means and Standard Deviations GROSS Variable FACTOR CODE .. MACHINE MACHINE MACHINE MACHINE MACHINE MACHINE For entire sample 1 2 3 4 5 6 Mean Std. Dev. 43734.442 66217.058 58863.293 46476.658 50966.202 49835.116 51867.818 26251.437 31800.716 34550.464 23827.613 29937.978 24619.856 29301.112 3056 3153 7888 7747 15575 9721 47140 Mean Std. Dev. N ---------- .. Variable ST-AXLE FACTOR CODE MACHINE MACHINE MACHINE MACHINE MACHINE MACHINE For entire sample 1 2 3 4 5 6 ---------- * * ANALYSIS OF VARIANCE -- DESIGN .. EFFECT MACHINE ~ultivariateTests of Significance (S Test Name Pillais Hotellings Wilks Roys Value .05253 .05471 .94781 .04499 1 * * = 2, M = 1 ,N = 23565 1/2) Approx. F Hypoth. DF Error DF Sig. of F 254.29326 257.86267 256.07784 94268.00 94264.00 94266.00 .OOO .OOO .OOO 10.00 10.00 10.00 ---------Univariate F-tests with (5,47134) D. F. Variable Hypoth. SS Error SS Hypoth. MS Error MS GROSS ST-AX LE 1.51543+12 3.89563+13 3.0307E+11 826496008 6.19823+10 1.75563+12 1.23963+10 37247512.2 F Sig. of F 366.69694 332.81005 .000 .OOO MANOVA BY MACHINE (OLD VS. NEW) cases accepted. cases rejected because of out-of-range factor values. cases rejected because of missing data. non-empty cells. 47140 7673 0 2 1 design will be processed. ---------Cell Means and Standard Deviations GROSS Variable FACTOR CODE .. Mean Std. Dev. MACHINE OLD MACHINE NEW For entire sample ---------- .. Variable ST-AXLE FACTOR CODE Mean Std. Dev. N MACHINE OLD MACHINE NEW For entire sample ---------- * * ANALYSIS OF VARIANCE -- DESIGN 1 * * .. EFFECT MACHINE Multivariate Tests of Significance (S = 1, M Test Name Pillais Hotellings Wilks Roys Value .02172 .02221 .97828 = 0, N = 23567 1/2) Approx. F Hypoth. DF Error DF Sig. of F 523.38268 523.38268 523.38268 47137.00 47137.00 47137.00 .OOO .OOO .OOO 2.00 2.00 2.00 ,02172 ---------Univariate F-tests with (1,47138) D. F, Hypoth. SS GROSS 5.77913+11 3.98943+13 5.77913+11 846313461 3.32203+10 1.78443+12 3.32203+10 37854503.0 ST-AXLE Error SS Hypoth. MS Error MS Variable F Sig. of F 682.85184 877.58151 .OOO .OOO MANOVA BY MACHINE WITH ROUTE AS COVARIATE 47140 7673 0 6 cases accepted. cases rejected because of out-of-range factor values. cases rejected because of missing data. non-empty cells. 1 design will be processed. ---------CELL NUMBER Variable MACHINE 1 2 3 4 5 6 1 2 3 4 5 6 Cell Means and Standard Deviations GROSS Variable FACTOR CODE .. MACHINE MACHINE MACHINE MACHINE MACHINE MACHINE For entire sample Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. 1 2 3 4 5 6 - - - - - - - - - - .. Variable ST-AXLE FACTOR MACHINE MACHINE MACHINE MACHINE MACHINE MACHINE For entire sample CODE 1 2 3 4 5 6 - - - - - - - - - - .. Variable ROUTE FACTOR MACHINE MACHINE MACHINE MACHINE MACHINE MACHINE For entire sample CODE 1 2 3 4 5 6 * * ANALYSIS OF VARIANCE -- DESIGN .. EFFECT WITHIN CELLS Regression Multivariate Tests of Significance (S Test Name Pillais Hotellings Wilks Roys Value .00186 .00186 .99814 .00186 1 * * = 1, M = 0, N = 23565 ) Approx. F Hypoth. DF 43.80448 43.80448 43.80448 2.00 2.00 2.00 Error DF Sig. of F 47132.00 47132.00 47132.00 .OOO .OOO .OOO ---------Univariate F-tests with (1,47133) D. F. Variable GROSS ST-AXLE Sq. Mul. R .R .00058 .00184 .02412 .04295 F Sig.ofF 27.44714 87.11385 .OOO .OOO Variable GROSS ST-AXLE Mu1 Ad j . R-sq. Hypoth. MS Error MS .00056 22672231249 826032516.7 .00182 3238856747 37179585.08 ---------Regression analysis for WITHIN CELLS error term Dependent variable GROSS .. COVARIATE ROUTE COVARIATE B 409.39553 Lower -95% Beta Std. Err. t-Value Sig. o f t .024 12 78.144 5.239 .OOO Beta Std. Err. t-Value Sig. of t .04295 16.579 CL- Upper ROUTE 256.233 562.559 Dependent variable ST-AXLE .. COVARIATE ROUTE COVARIATE ROUTE B 154.73617 Lower -95% 122.242 CL- Upper 187.230 9.333 ,000 * ANALYSES OF VARTANLX -- DRSTGN . CTTECT . MACKINC Multivariate T e s t s of S i g n l f i c a n c - e Pill ais fiotellings I i ~ l l ; ~ Roys 2 - 3, X - x Appl-ox. F Hypoth. hE' value T e s t Name (S 1 .P4405 .04SCS 213.37980 214.33079 10.00 16.00 .95623 .0361P 213.92526 I . h 1 1 - ? ~ r ~ c . r \~ - 0 P S l q , nl @47(~0-00 , 0 4 ? 6 > .On *43h4.00 : C ? (' . Ct'C 0 ( 7 (' ---------Univariate F - t e s t s with ( 5 , 4 7 1 5 3 ) D. P. Error SS Rypdth. MS ki-l-cl>.ks Variable Hypoth. SS GROSS 1.2297B+12 3 . 8 9 3 3 E + 1 3 2 . 4 4 9 4 1 < + 1 1 $ 3 6 0 3 3 4 1 ; 367.7 ?ti77 4.9873~+10 1 , 7 5 2 4 ~ 4 1 3 9 9 ' 7 4 6 6 0 6 3 7 3 2 1 7 6 4 ~ 1 3 . 1 3 6 n . > R 1 7 - S'i-AXLE - - - - - - - - - - * * ANALYSIS OF VARIANCE -- DKSfGN .. EFFECT CONSTANT M u l t i v a r i a t e T e s t s of Significance ( S Value T e s t Name Pillais Hotellings Wilks Roys .55454 .64328 \ * - \ I .Z. 1 11 . A , M - 0 , N - 33kinh ) Approx, P' t l y p ~ l t l ~I)P , 1~0~0,a994 2'00 1JOGU , 2 9 9 4 2 , 13068.2994 0 0 l?k.t.z\v \\I:' s\q. 4 7 1 > 3.Or1 111 33.Ut) 4'11 3 3 . t ) t l rjl Y, .t\~\t\ . 0rll) . 1)1JIi .35672 ---------U n i v a r i a t e F-tests with (1,47133) I], F, Variable Hypoth. SS GROSS 2.12463+13 3.51393+11 ST-AXLE Error f3lJ Ilypotll, M U kt-t.ut M9 I: :;Id, 3.0933E+13 2,I24Cfilj1 0 2 f i b 1 % 9 1 . / % 4 / 7 I , I l L I , M 1.7524E.CI2 3 . 5 1 3 9 f i l 1 1 I - / l'/tl9Otl. l 4 4 9 l . l ( l h ? d - - - - - - - - - Adjusted and Estimated M e a n ~ Variable GROSS .. CELL O b s . Mean Adj, Mean R a t , lrleatr Pevf R @ s i ( l . A t d . f / h ej t i . Adjusted and Estimated Means (CONT.) Variable ST-AXLE CELL Est. Mean Obs. Mean Adj. Mean .. Raw Resid. Std. Resid. MANOVA BY MACHINE (OLD VS. NEW) WITH ROUTE AS COVARIATE (INTERSTATES ONLY) cases accepted. cases rejected because of out-of-range factor values. cases rejected because of missing data. non-empty cells. 47140 7673 0 2 1 design will be processed. ---------CELL NUMBER Variable MACHINE 1 2 1 2 Cell Means and Standard Deviations GROSS Variable FACTOR CODE .. Mean Std. Dev. CODE Mean Std. Dev. CODE Mean Std. Dev. MACHINE OLD MACHINE NEW For entire sample ---------- .. Variable ST-AXLE FACTOR MACHINE OLD MACHINE NEW For entire sample - - - - - - - - - - .. Variable ROUTE FACTOR MACHINE OLD MACHINE NEW For entire sample ---------- * * ANALYSIS OF VARIANCE -- DESIGN 1 * * .. EFFECT WITHIN CELLS Regression Multivariate Tests of Significance (S = 1, M = 0 , N = 23567 ) Test Name Pillais Hotellings Wilks Roy s Value .00651 .00656 .99349 .00651 Approx. F Hypoth. DF Error DF Sig. of F 154.51684 154.51684 154.51684 47136.00 47136.00 47136.00 .OOO .OOO 000 2.00 2.00 2.00 . * * ANALYSIS OF VARIANCE -- DESIGN 1 * * .. EFFECT CONSTANT Multivariate Tests of Significance (S = 1, M = 0, N = 23567 ) Test Name Value Pillais Hotellings Wilks Roys Approx. F Hypoth. DF .36656 13638.1263 .57867 13638.1263 .63344 13638.1263 .36656 2.00 2.00 2.00 Error DF Sig. of F 47136.00 47136.00 47136.00 .OOO .OOO .OOO - - - - - - - - - Univariate F-tests with (1,47137) D. F. Variable Hypoth. SS Error SS Hypoth. MS Error MS GROSS ST-AXLE 2.24903+13 3.97043+13 2.24903+13 842320893 26700.4973 3.95673+11 1.77543+12 3.9567E+11 37664410.4 10505.0106 F Sig. ---------Adjusted and Estimated Means Variable GROSS A d j . Mean CELL Obs. Mean .. Est. Mean Raw Resid. Std. Resid. Adjusted and Estimated Means (CONT.) ST-AXLE Variable CELL Obs. Mean A d j . Mean Est. Mean Raw Resid. Std. Resid. ---------- .. 4928 BYTES OF WORKSPACE NEEDED FOR MANOVA EXECUTION. APPENDIX G Site Notes FORENSIC.01 88/10/06 FORENSIC W I M S I T E 1 ON US-93 AT MP 0 3 5 . 2 07:OO:OO S B & 0 4 7 . 5 NB S E T S B AT MP 0 3 5 . 2 ON DIVIDED HIGHWAY TWO LANES EACH WAY I N SLOW LANE. MACHINE 0 3 4 9 - 0 0 0 3 WITH MAT 2 0 7 AND TWO TEMPORARY LOOPS 6 'X 6 ' , 1 6 ' LEADING EDGE TO LEADING EDGE. LOOPS HAVE 4 TURNS EACH & NO NAILS LEFT AT CORNERS. BLACK PUTTY USED AT CORNERS OF LOOPS AND I N CENTER OF EACH S I D E . DUCT TAPE USED OVER P 4 6 PRIMER. P46 TAKES TOO LONG TO GET TACKY, STAYS SLIMY. S I T E NUMBER 0 0 0 3 0 0 0 1 . S E T NB AT MP 0 4 7 . 5 ON SPEED LOOPS. MAT RPM06 WITH CORRECTION FACTOR 1 3 2 . ROAD I S 2 LANES, 1 NB & 1 SB. MACHINE 0 3 8 1 - 0 0 7 4 WITH LOOPS 1 8 ' . S I T E NUMBER 0 0 7 4 0 0 0 1 . NORTHBOUND MACHINE LOOKS OK AND S T I L L WORKING BUT ONLY 3 0 0 RECORDINGS, SO NO RETRIEVE DONE. SOME SOUTHBOUND STATION I S LIKEWISE-OK AND NO RETRIEVE. 15:OO PICKED UP BOTH STATIONS. RETRIEVED BOTH.... S B MACHINE HIKE CAUSE THERE I S NO CONFIG 4 7 DATA I N THE MACHINE. RETRIEVED NB INTO FILE FORENSIC.01N TOOK A NB OK. RESET S B WITH 0 3 8 1 - 0 0 1 4 . S I T E NUMBER 0 0 1 4 0 0 0 1 , MAT RPM06 WITH CORRECTION FACTOR 1 3 2 . ALL ELSE I S THE SAME AS ORIGINAL SET. PICKED U P S B & RETRIEVED OK INTO F I L E FORENSIC.01S. END S I T E . FORENSIC.02 88/11/03 FORENSIC WIM SITE 02 ON 1-40 AT MP 9 E 09:20 C W BOUND SET WB ON MACHINE 381-0074 WITH MAT 033/207 ON THREE TURN 6' x 6' LOOPS 18' LEADING EDGE TO LEADING EDGE TEMPS. SET El3 ON MACHINE 381-0014 WITH MAT RPM6/132 ON THREE TURN 6' X 6' LOOPS 18' LEADING EDGE TO LEADING EDGE TEMPS. RETRIEVED WB FILE TO FORENSIC.02A RETRIEVED EB FILE TO FORXNSIC.02B RETRIEVED WB TO FORENSIC.02C RETRIEVED EB TO FORENSIC.02D. EB LOOP A NOT OPERATING, END SITE FORENSIC.03 88/11/01 15: 00: 00 FORENSIC WIM SITE NUMBER 03 AT MP56 EAST AND WEST BOUND 88/10/31 14: 00 SET WB ON MAT 033/207 MACHINE 381-0014 ON 4 TURN LOOPS 6' x 6' 18' LEADING EDGE TO LEADING EDGE. SITE NUMBER 00140003 14:35 SET EB ON MAT RPM6/132 MACHINE 381-0074 ON 3 TURN LOOPS 6' x 6' 18' LEADING EDGE TO LEADING EDGE. SITE NUMBER 00740003 RESET TO CONFIG 44, ALL PARAMETERS MESSED UP 88/11/01 07:15 RETREIVE EB TO FILE FORENSIC.03A RETREIVE WB TO FORENSIC.03B 15:OO RETRIEVED EB TO FILE FORENSIC.03C END SITE RETRIEVED WB TO FILE FORENSIC.03D END SITE 89/05/31 08:30 FORENSIC STATION 3. EB SET WITH MACHINE #80 AND MAT RPM6 WITH A C.F. OF 132. SITE # 00800303. 18 FOOT LOOPS 6x6. WEATHER IS WINDY AND COOL. 1-40 M.P. 56.0. RUNNING AT 09:OO. 09:15 WB SET WITH MACHINE #74 AND MAT 207. 18 FOOT LOOPS 6x6. SITE # 00740307. RUNNING AT 10:35. 89/06/01 03:30 EB PICKED UP AT THIS TIME. NO ERRORS, NO PROBLEMS. 2300+ RECORDINGS WHICH CORRESPONDS TO MANUAL CLASSIFICATION OF APPROXIMA 100 TRUCKS PER HOUR. 10:45 WB PICKED UP AT THIS TIME. STATUS MODE 1 SHOWED 9 ERRORS AND MODE 2 SHOWED NOISE ON THE MAT (2's). LOOKS LIKE WE'RE DUE FOR A NEW OSCILLATOR AND/OR MAT. ONLY ABOUT 1800 RECORDINGS. FORENSIC.04 88/10/27 FORENSIC WIM SITE 04 AT MP 135 ON 1-40 EB & WB 08:OO:OO SET UP WB ON MACHINE 0381-0014 MAT 033/207 TWO 6' x 6' x 4 TURN TEMP LOOPS 18' LEADING EDGE TO LEADING EDGE. FLAT AFTER LONG UPHILL. SETUP EB ON MACHINE 0381-0074 MAT RPM6/132 TWO 6' x 6' x 4 TURN FLAT AFTER LONG TEMP LOOPS 18' LEADING EDGE TO LEADING EDGE. DOWNHILL. REPLACED WB MAT 033/207 WITH RPM9/127 BECAUSE MAT WAS IGNORING TRAFFIC AND SHOWING "L" FOR TEMPERATURE. RETRIEVED INTO FILE FORENSIC.04A RETRIEVED EB INTO FILE FOREMSIC.04B W B CF WAS NOT CHANGED AT 7:30. RESET CF FROM 207 TO 132. RETRIEVED INTO FILE FORENSIC.04C RETRIEVED EB INTO FORENSIC.04D RETRIEVED WB INTO FORENSIC.04E END SITE RETRIEVED EB INTO FORENSIC.04F END SITE FORENSIC.05 88/10/26 FORENSIC WIM SITE 05 AT MP 179.7 EB & WB ON 1-40 09: 15:00 SET WB ON MACHINE 0381-0074 WITH MAT RPM6/132 SITE 00740099. LEFT DOWN TRAFFIC SIDE OF MAT FREE OF NAILS. P46 PRIMER USED ON ONE TEMP LOOP 18' LEADING EDGE TO LEADING EDGE & ON PERIMETER OF MAT FOR TAPE ADHESION. 6 ' x 6' LOOPS 3 TURNS ON PERM LOOP AND 4 TURNS ON TEMP. SET EB ON MACHINE 0381-0014 WITH MAT RPM9/132 SITE 00140099. LEFT DOWN TRAFFIC SIDE OF MAT FREE OF NAILS. P46 PRIMER USED ON ONE TEMP LOOP 18' LEADING EDGE TO LEADING EDGE & ON PERIMETER OF MAT FOR TAPE ADHESION. 6 ' x 6' LOOPS 3 TURNS ON PERM LOOP AND 4 TURNS ON TEMP. RETRIEVED WE INTO FORENSIC.05A RETRIEVED EB INTO FORENSIC.05B TOO HEAVY. SCAN OF DATA SHOWS HEAVY TRUCKS, RETRIEVED WB INTO FORENSIC.05C END SITE RETRIEVED EB INTO FORENSIC.06D END SITE FORENSIC.06 88/09/13 FORENSIC WIM SITE #06 1-40 EAST OF WINONA INTERCHANGE 14:OO:OO 11:45 WB SETUP. OSC 2,3 FAILED WITH MAT 207 ON TESTER. OSC 1 MAT 207 MACHINE 0381-0014. STATUS MODE 2 SHOWED "0" ON TEMP BUT IT WORKS. LOOPS ARE SPEED SITE 18'. NO PRIMER USED ON MAT. MP 212 SITE #03496002. 12: 15 START WB 12:20 EB SETUP. OSC 2,3 FAILED WITH MAT 157 ON TESTER. OSC 4 MAT 157 MACHINE 0349-003. TEMPORARY LOOPS 18' X 6' WTTH PRTMER & R U C K SCOTCH RUBBER TAPE WITH SCOTCH FOAM, 4516 (1/16") & 4508 (1/8" ) UNDER LOOP AT LEADING EDGE. MP 211.9 SITE # 00036001. BATTERY MACHINE 0349-005 IS JUNK. IT DOES NOT KNOW THAT DOWN TO 5.5V. IT HAS LOOPS & MAT ATTACHED. 13:45 START EB 16:45 BATTERY OUT ON EB. REPLACED WITH JUNK MACHINE. ALL DATA RETRIEVED TO FORENSIC.06A 30 MINUTES SLOW. 17:OO WB RETRIEVED TO FORENSIC.06B 07:15 RETRIEVED EB TO FORENSIC.06C TEMPERATURE OVERNIGHT WAS BELOW 32'. LOOPS W O K GOOD. 07:20 RETRIEVED WB TO FORENSIC.06D 1o:oo EB & WB CHECKED. EB VOLTAGE UP TO 5.9V. 13 :45 EB RETRIEVED TO FORENSIC.06E BATTERY VOLTAGE UP TO 6.0VOLTS. SOME WEAR ON RUBBER TAPE LOOP A AT CROSSOVER POINT WHERE LEAD-IN JOINS LOOP. STATUS MODE 1 HAD 1 ERROR SHOWING. END SITE. 14:OO WB RETRIEVED TO FORENSIC.06F END SITE. FORENSIC.08 88/11/09 FORENSIC WIM SITE .08 EB AND WB AT MP 319.5 SET EB ON MACHINE 381-0074 ON MAT RPM6/132 ON 2 TEMPS 3 TURNS 16 FOOT LEADING EDGE TO LEADING EDGE SET WB ON 381-0014 ON MAT 033/207 ON PERM LOOPS 18 FOOT LEADING EDGE TO LEADING EDGE STAT. MODE 2 DISPLAYED 010 FOR LOOPS AND MAT REPLACED WITH MACHINE 349-0003. STATUS MODE 2 DISPLAYED 101; REPLACED WITH MACHINE 349-0005. DISPLAYED ---. RETRIEVED EB ON FORENSIC.08A. RETRIEVED WB ON FORENSIC.083. STATUS MODE 2 DISPLAYED 000 MAT ACTUATING FIRST THEN LOOPS. RECORDINGS 1 ENTERED TO RESTART LOOP BOARD LOST COMMUNICATION. STATUS WENT TO 2 ERRORS AND IT STARTED WORKING. -- RETRIEVED FORENSIC.OBC. INOPERATIVE. STATUS MODE 2 011 LOOP B AND M A T RETRIEVED EB INTO FORENSIC.O8D, END EB. MCVED 381-0014 TO WB. RETRIEVED 381-0074 INTO FORENSIC.08E. TEST READING ON PRIMITIVE TRIQUARTER 67.6 ON LOOPS AND 102.6 ON MAT. RETRIEVED WB FILE TO FORENSIC.08F. FOUND A TWISTED MASS OF METAL THAT USED TO BE A FLANGE FOR THE MAT. RETRIEVED WB TO FORENSIC.08G. END WB END OF SITE. 89/05/10 08:30 STATION 09 ON 1-40 AT M.P. 343.0. BOTH SIDES ON TEMPORARY LOOPS 16 FEET AND 6x6. PAVEMENT IS FAIR, WEATHER CLEAR. EB SET WITH MACHINE #80 AND MAT #RPM6. SITE #00800901. UP AND RUNNING AT 08:45 WITH NO PROBLEMS. COULD NOT NAIL DOWN OSCILLATOR COVER BUT IT IS TAPED DOWN PRETTY WELL. 09:45 WB SET WITH MACHINE #74 AND MAT 207. WHEN COMMUNICATION WAS FIRST ESTABLISHED WE SAW THAT THE WEIGHMAN HAD RESET COMPLETELY.?? ALL NUMBERS PLUGGED INTO THE WEIGHMAN AND IT LOOKS OK. RUNNING AT 09:50. 89/05/11 08:45 RETRIEVED EB. STATUS MODE 1 SHOWED 1 ERROR BUT IT ALSO COLLECTED 2100+ RECORDINGS. FILE DUMPED TO FORENSIC.09E. OSCILLATOR COVER WAS STILL IN PLACE. 09:50 RETRIEVED WB INTO PORENSIC.09W. NO ERRORS AND 2100+ RECORDINGS. FORENSIC.10 89/03/13 FORENSIC WIM STUDY STATION 10 AT MP 14.0 ON 1-10 06:30:00 BOTH SIDES HAVE A NEW LOOP CUT INTO FRESH AC BASE. MILLING OF THE SLOW LANE PROMPTED THE REPLACEMENT OF LOOPS. SIGNING, BARRICADES, CONES ON EAST BOUND SLOW LANE START THE TAPER TO FAST LANE AT EAST BOUND SITE SO THAT ONLY 3/4 OF MAT IS EXPOSED TO 6' x 6' 16' SEPARATION SECOND LOOP TEMPORARY. BOTH TRAFFIC. MACHINES HAD RESET, SITE#, DATE, TIME, RECORDINGS, INTERVAL, START DATE, START TIME, CONFIG, THRESHOLDS PARAMETERS. #74 HAD RESET LAST 9 HOURS EARLIER AND #73 11 HOURS. MILLING PROCEEDING EAST OF SITE, SIGNING WILL PREVENT COUNT UNTIL DAY'S WORK IS DONE. EB SET WITH MACHINE 381-0074 SITE 00740010 MAT RPM6 CF 132. WB SET WITH MACHINE 381-0073 SITE 00730010 MAT 033 CF 207. RETRIEVED OVER 1000 RECORDINGS IN WB TO FILE FORENSIC.1OA IN LESS THAN 5 MINUTES. EB, WELL THAT A STORY ALL BY ITSELF. THE SIGNING WAS EXACTLY WHERE IT WAS YESTERDAY. IT MAY NOT HAVE MOVED AT ALL. HARDLY ANY TRAFFIC WAS CROSSING OVER THE MAT. THE MACHINE SHOWED 9 ERRORS AND 883 RECORDINGS(MAYBE YES/NO). STARTED RETRIEVING AT 9:50,IT SHOWED THAT IT WAS RETRIEVING TO FILE 2 (------ 2) AT 10:15 I CANCELED THE RETRIEVE. 883 WE HAVE RECORDINGS SHOULD NOT TAKE 25 MINUTES TO RETRIEVE. EXPERIENCED THE SYMPTOM OF NON-STOP RETRIEVE IF THE LOOPS OR MAT WAS DISCONNECTED WHILE A RETRIEVE WAS IN PROGRESS. THIS WAS NOT THE CASE THIS TIME. I THEN DISCONNECTED THE MAT AND LOOPS JUST TO TRY AND GET SOMETHING TO WORK. NO LUCK. I WATCHED IT SHOW A RETRIEVE TO FILE 2 FOR ANOTHER 20 MINUTES AND THEN DID A RECORDING "0" TO THE WEIGHMAN. BY THE WAY, WE CANNOT DO A TOTAL RETRIEVE OF THE 381-0073,4 WEIGHMAN MACHINES. IT USES 107% OF THE RETRIEVER ELITE MEMORY. UNLIKE SOME PEOPLE, THE RETRIEVE2 IS SMART ENOUGH TO KNOW THAT 10 POUNDS WILL NOT FIT INTO A 5 POUND SACK. ...... CHECKED OUT LOANER MACHINE FROM GOLDEN RIVER 3 8 1 - 0 0 1 4 FOR TOTAL RETRIEVE WITH MACHINE COLD STARTED (BATTERY REMOVED, POWER SUPPLY USED TO POWER UP) & RETRIEVER E L I T E SHOWED 9 9 % I N CONFIG 4 7 & ONLY TOOK 1 0 : l O WHY I S MACHINE # 1 4 99% O F RETRIEVER MEMORY AND # 7 3 , # 7 4 107%??? . S I T E P I C K E D UP. END S I T E I N SHOP; E B RETRTEVED TO F I L E FORENSIC. 1OB. 9 ERRORS SHOWING I N STATUS MODE 1, DIRECTION DOES NOT HAVE 2 4 HOURS. WB RETRIEVED T O FORENSIC.1OC. 9 ERRORS SHOWING I N STATUS MODE 1. 89/05/16 08:20 EB SET WITH MACHINE #74 AND MAT 207 AT M.P. 41.0 1-10. WEATHER COOL, LOOKS LIKE RAIN. TEMPORARY LOOPS 6x6 AND 16 FEET. NO PROBL SO FAR. UP AND RUNNING AT 08:30. SITE #00741101. 09:20 WB SET WITH MACHINE #80 AND MAT RPM6. MACHINE #80 HAD 1 ERROR SHOWING BEFORE IT WAS SET. A 3 CLEARED THE FAULT AND THE TIME WAS SPRINKLING NOW, HOPEFULLY WE GOT IT DOWN BEFORE THE PAVEMENT WAS WET. SITE #00801105. RUNNING AT 09:30. 89/05/17 08:45 EB PICKED UP AT THIS TIME WITH NO ERRORS AND 2200+ RECORDINGS. LOOKS OK. 09:30 WB WORKING BUT SOMETHING IS SCREWY. ONLY 700+ RECORDINGS RETRIEVED AND DUMPED TO DISK AND DISCOVERED THAT NO RECORDINGS HAD BEEN MADE BETWEEN 18:20 AND 09:OO. HOOKED UP TEST BOX TO MAT OSCILLATOR AFTER SEEING 2's ON STATUS MODE 2. TEST BOX SAYS SOMETHING IS WRONG. TIGHTENED OSCILLATOR AND RECHECKED - STILL NO GOOD. CHANGED MATS AND OSCILLATOR BUT STILL CAN'T GET A WORKING COMBINATION. PLACED MAT 207 ON THE GROUND AND TEST BOX AND WEIGHMAN SAY IT'S OK. RUNNING AT 10:35. 89/05/18 10:40 PICKED UP WB THIS TIME AND ALL LOOKS GOOD. NO ERRORS. 2000 SOME RECORDINGS. EB DUMPED TO FILE CALLED FORENSIC.11A WB DUMPED TO FILES CALLED FORENSIC.11B AND FORENSIC.11C 11B IS THE FIRST WB SET (THE PARTIAL) AND 11C IS THE LAST SET WITH MAT 207. FORENSIC. 012 88/07/15 12:30:00 1-10 WIM AT LITCHFIELD RD. FOR STATE WIDE PAVEMENT EVALUATION STUDY MODEL 381-0014 IS SET AND RUNNING FINE AT EB MP. 129.2 ON SPEED LOOPS ON MAT 207 OSCILLATOR I11 CORRECTION FACTOR 207, SITE NUMBER 10129003. MODEL 349-0003 IS SET AND NOT RUNNING RIGHT AT WB MP. 129.2 ON TEMPORARY LOOPS ON MAT 157 OSCILLATOR I CORRECTION FACTOR 132. RETRIEVED 381-0014 EB. SOME VEHICLES. 0349-0003 ll:35A FUNCTIONS OK MISSING 3081-0074 FUNCTIONS OK MISSING SOME VEHICLES. 0349-0005 NO GO POWER DOWN RESTART -- DASHES IN STATUS MODE 2 (LOOP & MAT & TEMP) LOOPS & MAT CONNECTED, RECORDINGS RESET 3 & 1 BOTH SUCCESSFUL ON AGAIN OFF AGAIN COUNT/RECORDING MISSING LOTS OF STUFF. 11:54 RECONNECT OF 3081-0014 TO MAT 207 & OSCILLATOR 111, MISSING SOME VEHICLES 3081-0074 ON MAT 157 WITH OSCILLATOR I IN TRAVEL LANE WITH TEMP LOOPS -- DASH IN STATUS MODE 2 FOR TEMP DISPLAY; OSCILLATOR I1 WITH TEST CAPACITOR AND TEMP LOOPS; DASH IN STATUS MODE 2 FOR MAT DISPLAY. 3049-0003 ON MAT 157 WITH OSCILLATOR I IN TRAVEL LANE WITH TEMP LOOPS; A IN TEMP DISPLAY CHANGE TO DASH; NO MAT DISPLAY; LOOPS QUESTIONABLE. OSCILLATOR I1 WITH TEST CAPACITOR AND TEMP LOOPS TEMP DISPLAY BUT NO MAT DISPLAY. -- TWO OSCILLATORS (I, 11) BROUGHT BACK TO SHOP FOR REPAIR. OSCILLATOR I1 FOUND TO HAVE AN OPEN INTERNAL CONNECTION & REPAIRED RESET WB WITH MAT 157 AND OSC I1 WITH TEMPORARY LOOPS. 3081-0074 SITE NUMBER 00000000. WORKING OK. EB CHECKED AND FOUND TO BE MISSING SOME TRAFFIC, GETTING MOST. OSCILLATOR I TESTED AND FOUND TO WORK, HOWEVER TEMP READOUT IS FLAKY. RETRIEVED WB AND EB. BOTH WORKING RETRIEVED WB TO FORENSIC.12A RETRIEVED WB MACHINE DOES RESET EB MAT SPORADICALLY. AND EB. BOTH WORKING. EB MISSING RANDOMLY. NOT LIKE LOOPS, THEN OTHER TIMES IT'S THE MAT. LONG NAILS CAME OUT IN HEAT. MISSING AT 10A RETREIVED BOTH SIDES. -- RETRIEVED WB TO FORENSIC.12B RETRIEVED EB TO FORENSIC.12C RETRIEVED EB TO FORENSIC.12D RETRIEVED WB TO FORENSIC.12E RETRIEVED EB TO FORENSIC. 12G RETRIEVED WB TO FORENSIC.12F RETRIEVED AND PICK UP BOTH SIDES. END STUDY AT LOCATION 12 ONE TEMP LOOP 18 ' FROM ONE PERM LOOP SITENUMBER 00000000 = WEST BOUND. ONE TEMP LOOP 18' FROM ONE PERM LOOP SITENUMBER 10129003 = EAST BOUND forensic.13 forensic wim site 13 89/04/ 14 16 FOOT LOOPS 6x6. SET TEMPORARY LOOPS AT M.P. 180.0 EB WITH MAT 207 AND MACHINE #74. RETRIEVER SHOWED 00- ON STATUS MODE 2 AND 9 ERRORS WITHIN 5 MINUTES. DISCOVERED WITH LEE'S COMPUTER THAT THERE WERE 27 ERRORS. WE THEN DISCOVERED WITH THE TEST BOX THAT WE HAD A BAD OSCILLATOR CORD AND CHANGED OSCILLATORS WITH ANOTHER MAT (132-RPM9) THEN STATUS MODE 2 SHOWED PROPER WORKING, BUT IT WOULD NOT RECORD TRAFFIC. WE SWITCHED MACHINES AND NOW #73 IS HOOKED UP AND GIVES SAME READINGS. WE THEN SWITCHED LOOPS A TO I3 AND IT TOOK OFF WORKING. SITE #00731301 . WB SET WITH LEE'S TEMPORARY LOOPS, NEW MACHINE #80, AND NEW MAT. CORRECTION FACTOR IS 255 AND TEMPERATURE COEFFICIENT IS 8. SITE #00801305. WEIGHTS APPEAR HEAVY, LEE SAYS THAT 255 IS PROBABLY NOT THE CORRECT NUMBER. NEW CORRECTION FACTOR OF 245 ENTERED BY LEE. STILL LOOKS HIGH. LEE NOW PLAYING WITH COMPUTER AND MACHINE #80 TO LOOK AT REALTIME DISPLAY FOR UPDATING CORRECTION FACTOR. EDUCATED GUESSING. NOW HAVE CF OF 200. LOOKS A LOT BETTER. ALSO SET UP NEW MARKSMAN 600- IT IS LOCKED UP, CANNOT ALTER PARAMETERS. LEE PULLED BATTERY AND SAYS IT IS LOW, 5.7 VOLTS. MACHINE WAS PICKED UP TO BE CHARGED IN SHOP. LOOPS ARE 6x6 AND 16 FEET. HOSES FOR MARKSMAN 600 ARE 10 FEET APART. ALSO DISCOVERED THAT THE MAT IS NOT A NEW ONE AND LEE DOESN'T KNOW WHAT THE CORRECTION FACTOR OR TEMPERATURE COEFFICIENT IS. BOTH WERE GUESSES. RETRIEVED EB TO FORENSIC.13E END DIRECTION RETRIEVED WB TO FORENSIC.13W END DIRECTION. END SITE FORENSIC. 15 89/03/17 15:OO FORENSIC WEIGH IN MOTION SITE NUMBER 15 AT MP 239.5 E 6 WB ON 1-10 EB SET ON 18' 6' x 6' SPEED LOOPS ON MACHINE 0381-0073 WITH MAT 033 CF 207 SITE NUMBER 00730015. THIS IS THE FIRST TIME THAT STATUS MODE 2 WORKS THE WAY WE THINK IT'S SUPPOSED TO. SHOWS 000 THAT GOES TO 111 WHEN A VEHICLE CROSSES. WB SET ON 18' 6' X 6' TEMPORARY LOOPS ON MACHINE 0381-0074 WITH MAT RPM6 CF 132 SITE NUMBER 00740015. STATUS MODE 2 SHOWS 00-. IF WE HAD SOME HARD COPY TO MATCH THE SOFTWARE, WE MIGHT BE ABLE TO FIGURE OUT WHAT IS GOING ON NOW. EB RETRIEVED TO FORENSIC.15B WITH JUST GOBS OF DATA. WB RETRIEVED TO FORENSIC.15Ar GOOD LUCK WITH THE DATA... ONLY 280+ RECORDS. BACK TO WB, THE DATE WAS WRONG AND I KNOW IT WAS RIGHT --IT WAS DOUBLE CHECKED WHEN THE MACHINE WAS SET UP WITH 9 ERRORS SHOWING WITH ERRATIC READOUT IN STATUS RECORDING 3. MODE 2. 2 ERRORS IMMEDIATELY AFTER RETRIEVE, & IT DID NOT ZERO RECORDINGS. DID A RECORDINGS 3 AND IT DID ZERO AND ERRORS CLEARED. THEN WITHOUT GETTING ANY COUNTS FROM TRAFFIC IT SHOWED 1 ERROR 2 MINUTES AFTER LAST RECORDINGS 3 WAS ENTERED. EB RETRIEVED TO FORENSIC.15Dr LOOKS OK. FORENSIC.lSC, NO GOOD. END SITE WB RETRIEVED TO FORENSIC SITE 18 EB SET WITH MACHINE #74 AND MAT FORENSIC SITE 18 AT M.P. 3 6 0 . 0 . 207 ON 1 6 FOOT LOOPS 6 x 6 . PAVEMENT RUTTED BUT FAIRLY SMOOTH. SITE #00741801. TEXT BOOK OPERATION-STATUS MODE 2 SHOWS 1's AND 0's. LOOKS OK. WB SET WITH MACHINE # 7 3 AND RPM 6 WITH CF OF 132 ON 16 FOOT LOOPS 6x6. SITE #00731805. RAN OUT OF OUR REGULAR TAPE AND LOOP B IS MADE WITH DUCT TAPE-WE'LL SEE HOW THIS WORKS WITH THE PRIMER. RUNNING AT 10:35. RETRIEVED EB AND ALL WAS WELL. 1300+ RECORDINGS, NO ERRORS. IS CALLED FORENSIC. 18E. FILE RETRIEVED WB AND OSCILLATOR CORD COVER WAS LOOSE AND FLOPPING AROUND. THE DUCT TAPE WORKS OK WITH PRIMER, BUT BY ITSELF IS NO GOOD. 1300+ RECORDINGS AND 2 ERRORS SHOWING. THE FILE IS CALLED FORENSIC.18W. FORENSIC S I T E 19 WIM STATION 19 S E T AT K.P. 4 6 . 0 WITH MAT RPM6 CORRECTION FACTOR 1 3 2 AND DEFAULT TEMPERATURE COEFFICIENT O F 30. MACHINE # 8 0 AND S I T E # 0 0 8 0 1 9 0 3 . U P AND RUNNING AT 1 1 : 4 0 . NB S E T WITH MAT 2 0 7 AND L E E ' S MACHINE # 1 4 WITH VERSION 1 0 FIRMWARE ON LOOP BOARD. S I T E # 0 0 1 4 1 9 0 7 . U P AND RUNNING AT 1 2 : 50. BOTH S I D E S S E T ON TEMPORARY LOOPS 1 6 FEET AND 6x6. RETRIEVED S B AND I T S T I L L LOOKED OK. I T HAD 5 7 8 RECORDINGS AND APPEARED TO BE DOING OK. NB SAME WAY. I T HAD 511 RECORDINGS. RETRIEVED F I L E S DUMPED ONTO D I S K AS FORENSIC. 19s FOR SOUTH BOUND AND FORENSIC.19N FOR NORTH BOUND. FORENSIC SITE 20 89/05/03 BETWEEN GISS PARKWAY AND PORT OF ENTRY 1-8 WB SET FIRST WITH MACHINE #74 AND MAT 207 ON 16 FOOT LOOPS 6x6. DIDN'T LOOK GOOD AT FIRST, STATUS MODE 2 SHOWED A DASH FOR THE MAT BUT IT WAS WORKING. RESTARTED AND MODE 2 CAME UP LIKE IT SHOULD. MAYBE MAT 207 IS BEGINNING TO FAIL? RUNNING OK AT 07:45. SITE #00742005. EB SET WITH MACHINE #80 AND RPM 6 ( C . F . 132) ON TEMPORARIES. ERRORS OR PROBLEMS. SITE #00802001. RUNNING AT THIS TIME. WB UP AT THIS TIME. NO ERRORS WITH 500+ RECORDINGS. TO FORENSIC.20W. SITE 00742005. NO FILE DUMPED EB PICKED, UP AT THIS TIME WITH NO ERRORS. FILE DUMPED TO FORENSIC.20D. FORENSIC S I T E 2 2 E B S I T E 2 2 S E T ON I 8 AT M.P. 1 0 5 . 0 WITH MACHINE # 7 4 AND MAT RPM6 ( C . F . 2 0 7 ) ON TEMPORARY LOOPS 1 6 FEET AND 6 x 6 . ALL I S WELL AND WORKING CLEANLY AT 1 0 : 4 0 . S I T E # 0 0 7 4 2 2 0 1 . WB S E T WITH MACHINE #80 ON PERMANENT S P E E D LOOPS, SQUARE, 1 8 F E E T , 6x6. S I T E # 0 0 8 0 2 2 0 5 . MAT # 2 0 7 . OPENED TO T R A F F I C AT 1 1 : O O AND T H I S ONE LOOKS OK TOO. P I C K E D U P E B AND FOUND NO ERRORS AND STATUS MODE 2 SHOWED ALL l t S . 5 0 0 + RECORDINGS. LOOKS OK. E B F I L E CALLED F O R E N S I C . 2 2 E . WB P I C K E D UP WITH 9 ERRORS SHOWING ON STATUS MODE 1, BUT I T APPEARS TO BE WORKING. 6 0 0 + RECORDINGS. F I L E CALLED FORENSIC.22W. FORENSIC.23 NO REPORT. FORENSIC. 2 4 88/07/20 FORENSIC WIM ST-85 AT MP 149 N & S BOUND NB SET ON MACHINE 349-0003 18' LOOPS SITE 85010003. MACHINE 381-0074 18' LOOPS SITE 85050074 RETRIEVED NB FORENSIC.24B TO FILE FORENSIC.24A. RETRIEVED SB SET ON S B TO FILE FORENSIC SITE 25 SET EB US 60 AT M.P. 206.0 WITH WIM #073 AND MAT #207 AND WB US 60 AT M.P. 206.0 WITH WIM #074 AND MAT #132. BOTH MACHINES NO PROBLEMS. WORKED AT THE START -- RETRIEVED BOTH MACHINES AND BOTH ARE STILL WORKING, BUT WB MACHINE #074 HAS 9 OR MORE ERRORS. SCANNING THE DATA FROM BOTH MACHINES IT APPEARS TO BE OK FOR EB, BUT WB LOOKS LIKE IT MAY HAVE BAD DATA. FORENSIC.26 89/02/27 WEIGHING IN MOTION FORENSIC STUDY STATION 26 ON SR 87 13:OO NB SET AT MP 200.2 MACHINE 381-0073 MAT 033 CF 207 ON 6' x 6' 16' LEADING EDGE TO LEADING EDGE. MACHINE HAS 9 ERRORS AND RESET TIME DATE & CONFIG 9 HOURS AGO SET AT 10:30 SB SET AT MP 199.1 MACHINE 381-0074 MAT RPM6 CF 132 ON 6' x 6' 16' LEADING EDGE TO LEADING EDGE. TEST BOX SAYS LOOPS AND MAT OK. MACHINE HAS 5 ERRORS AND RESET DATE AND TIME CONFIG 10 HOURS AGO NB MACHINE #73 (SITE NUMBER 00730026) APPEARED TO BE WORKING OK BUT SHOWED 9 ERRORS. SB MACHINE #74 (SITE NUMBER 00740026) ALSO APPEARED TO BE WORKING OK BUT SHOWED 00- ON THE DISPLAY (STATUS MODE 2) AND ALSO SHOWED 9 ERRORS. IT WOULD BE NICE TO KNOW WHAT STATUS MODE 2 IS FOR. FORENSIC.27 88-11-29 FORENSIC WIM STUDY #27 1-17 MP 233.4 11:30 88-11-29 11: 15 SET UP 381-0014 WITH MAT 033/207 ON PERM SPEED LOOPS NB 18 FEET APART, SITE #0014-0027 88-11-30 11: 15 ON-SITE INSPECTION REVEALED A PICKUP CLASSED AS A 5 AND A 3S2 CLASSED AS A 4. 900+ RECORDINGS MADE, AND IT WAS STILL WORKING. RETRIEVED OK. 12:oo SETTING UP SOUTHBOUND SITE (M.P. 223.65) SHOWED MULTIPLE ERRORS ON WEIGHMAN. INSTALLATION IS ONE PERMANENT LOOP AND ONE TEMPORARY LOOP 18 FEET APART. SITE NUMBER IS STILL 00140027. 12: 15 BEGIN RECORDING.??? TEST PICKUP FIRST CLASSED AS 8. OH WELL, STARTED WORKING ON THE THIRD TRY. 12:16 FIRST 352 CAUSES TEMPORARY LOSS OF COMMUNICATION. A 6 THEN AS AN SB STATION 27 SET THIS TIME ON TEMPORARY LOOPS 6x6 AND 16 FEET. LOCATION IS M.P.242.0 1-17. WEATHER IS CLEAR AND HOT. MACHINE #74 IS WITH MAT RPM9 AND A C.F. OF 132. SITE #00742705. RUNNING GOOD AT 11:OO. LOOKS OK. NB SET AT NEW RIVER ATR ON PERMANENT LOOPS. 18 FEET. MACHINE #80 WITH MAT RPM6 AND CF OF 132. LOOKS OK. #00802701. RUNNING AT 12:lO. 6x6. SITE FORENSIC.28 88/ 10/ 19 14:lO:OO FORENSIC WIM SITE 28 AT MP 269.5 ON 1-17 SB AND MP 273.0 NB SETUP OF SB ON SLIGHT DOWNHILL WITH SHALLOW LEFT TURN. TRUCK WEIGHTS MAY BE HEAVY DUE TO TRUCK SHIFT OVER MAT. ALL 3 MACHINES TRIED ON MAT RPM9/132 WITH ONE COUNT LDOP AND ONE TEMP LOOP 5lx 6'THREE TURNS 18' LEADING EDGE TO LEADING EDGE. NO COMMUNICATIONS FROM ANY MACHINE. MALFUNCTIONING LOOP CONNECTOR CAUSED PROBLEM? SITE NUMBER 00140028. ALL PREVIOUS REMAINS. MISSING SOME VEHICLES, MAT ACTING UP NOW AND AGAIN. SETUP OF NB. 6'x 6' FOUR TURN TEMP LOOPS 18' LEADING EDGE TO LEADING EDGE. MAT 033/207 USED WITH SITE NUMBER OF 00740028. MISSING SOME VEHICLES. SLIGHT UPHILL. RETRIEVED NB INTO FILE FORENSIC.28A. RE-NAILED MAT DOWNSTREAM. RETRIEVED SB INTO FILE FORENSIC.28B RETRIEVED SB INTO FILE FORENSIC.28C. AGAIN. DROPPING SOME VEHICLES.??? END SB. MAT IS LOOSE RETRIEVED NB INTO FILE FORENSIC.28D. END SB. STATUS MODE 2 SHOWS ACTIVITY ON BOTH LOOPS AND MAT, BUT NO COUNT OR RECORDING IS MADE. MAYBE WHY SO LOW IN RECORDINGS.??? AFTER SCANNING DATA.... NEITHER DIRECTION IS RELIABLE. BOTH ARE ONLY A SAMPLE OF TRUE TRAFFIC. IT'S TWO MONTHS SINCE LEE HOCKERT RECEIVED OUR COMMENTS AND REQUESTS NOTHING IN RESPONSE. ENGLAND STATED THREE MONTHS BACK THAT "WE HAVE A FIX FOR YOUR SOFTWARE PROBLEM."....NOTHING FROM THEM EITHER SINCE. ..... WHEN LEE WAS HERE HE TOLD US TO SEND BACK ONE OF THE W I M S FOR REPAIR. WHAT'S THE POINT? ALL THE MACHINES ACT THE SAME WAY: 1 ) L O S S O F COMMUNICATION WHILE CONNECTED TO THE RETRIEVER. CURSOR CAUSES LX)SS?? MOVING ' 2 ) I N LEES WORDS " I T WORKS G.REAT, I T J U S T M I S S E S SMALL VEHICLES. " NOT TRUE, THEY A L L M I S S ALL CLASSES O F VEHICLES EVEN THOUGH STATUS MODE 2 SAYS I T SHOULDN'T. 3 ) R E S E T T I N G OCCURS ON A RANDOM B A S I S FOR ALL MACHINES. THE D E F A U L T S O F C O N F I G 4 4 AND A L L PARAMETERS P L U S T H E L O S S O F ANYTHING I N MEMORY HAS HAPPENED TO ALL MACHINES. w i m 2 9 . doc 88/08/24 F I E L D NOTES FOR F O R E N S I C WIM S T A T I O N 2 9 1-17 SOUTH O F S E T MAT A T S P E E D L O O P S L O C A T E D A T M P 3 3 5 . 0 0 FLAGSTAFF. 3 4 9 - 0 0 5 S E T AND NOT WORKING, LOOPS & MAT I N A C T I V E . REPLACED W I T H 3 0 8 1 - 0 0 1 4 S E T ON MAT 2 0 7 W I T H CORRECTION FACTOR 207 18 FOOT LOOP S E P A R A T I O N 6 FOOT LOOPS. CONFIGURATION 4 7 C L A S S 5 & ABOVE. CHECKED S P E E D LOOPS LOCATED AT M P 2 9 9 . 3 0 1-17 SOUTH O F FLAGSTAFF. ONLY COUNT L O O P S . FOUND TWO L O C A T I O N S F O R S B S I T E 3 3 7 . 0 0 CONCRETE, F L A T , NEED 2 TEMPORARY LOOPS 338.60 ASPHALT, U P - H I L L , NEED 1 TEMPORARY LOOP CHECKED NB S I T E I T ' S S T I L L WORKING!!! 3 4 9 - 0 0 0 5 T R I E D AND FAILED!!! S E T 3 4 9 - 0 0 0 3 AT 3 3 7 . 0 0 S B 1-17 SOUTH O F FLAGSTAFF. CORRECTION FACTOR O F 1 3 2 ON MAT 157 LOOP S E P A R A T I O N O F 1 8 ' 6 x 6 ' LOOPS. T I R E D O F W A I T I N G FOR J I M WATSON. W I L L P R O V I D E OUR OWN T R A F F I C CONTROL. F I L E NAMED W I M 2 9 . 0 0 1 I S NORTHBOUND MACHINE # 1 4 F I R S T R E T R I E V E . WE W I L L NOW COUNT T R A F F I C A T F L A G S T A F F ATR. SOUTHBOUND BEEN R A I N I N G FOR COUPLE HOURS NOW, WE D I D R E T R I E V E . MACHINE WAS WORKING U N T I L WE ARRIVED. T H E B LOOP HAD COME U P FROM WATER, T H E T A P E WASN'T HOLDING. ON S T A T U S MODE 2 B LOOP WAS I N A C T I V E . PULLED T H E DEAD LOOP O F F T H E ROAD AND P I C K E D U P T H E MACHINE BUT L E F T THE MAT. MAYBE I T W I L L DRY OUT. HAH! THE SOUTHBOUND F I L E I S CALLED W I M 2 9 . 0 0 2 . NORTHBOUND I S S T I L L CHUNKING AWAY AND T H E F I L E I S CALLED W I M 2 9 . 0 0 3 . S B S T I L L WET. CANNOT P U T NEW TEMPORARY LOOP DOWN A T T H I S T I M E . NB RETRIEVED, CALLED IT WIM29.004, STATION PICKED UP. INSTALLED NEW SB LOOP WITH ADHESIVE PRIMER PAINTED ON ROAD AND STUCK DOWN WHITE REFLECTORIZED TAPE PAINTED BLACK. PRIMER WAS USED AROUND MAT ALSO TO SEE WHAT HAPPENS TO DUCT TAPE ON MAT IN RAIN. MACHINE HAD 2 ERRORS IN IT,STATUS MODE 1. COUNT WAS RESET TO 0. ERRORS WERE CLEARED, RECORDINGS 3,O. CHECKED SB STATION. WORKING FINE. METALIZED STRIPING TAPE SPLITTING ALONG LOOP LINES. CAN SEE RED WIRE SHOWING. CHECKED AND RETRIEVED, IN THE RAIN. WORKING GOOD. LOOP TAPE NEEDS TO BE HEAVIER QUALITY. ALL WIRES EXPOSED ALTHOUGH NOT MOVING AROUND. FILE WIM29.005. RETRIEVED SOUTHBOUND MACHINE BUT IT ONLY HAD 300 SOME RECORDINGS. INDUCTANCE AND RESISTANCE LOOKED OK BUT INSULATION RESISTANCE WAS ABOUT 2 MOHMS. PULLED STATION. SCANNING DATA SHOWED THAT IT WORKED, SORT OF, UNTIL 5A. DENIS DECIDED THAT IF THE TOTAL WAS NOT ENOUGH THEN IT CAN BE RESET. REPLACED B LOOP. MAYBE WE CAN ACCUMULATE ENOUGH DATA TO FULFILL THE 24 HOUR REQUIREMENT. LOOKS OK. MACHINE LOOKS OK. IT'S NOT RAINING YET BUT PROBABLY WILL. NO RETRIEVE AT THIS TIME BECAUSE ONLY ONE HUNDRED OR SO RECORDINGS. WILL TRY THIS AFTERNOON. RETRIEVED SOUTHBOUND AND DUMPED INTO FILE CALLED WIM29.007. LOOKS OK AND NOT TOO LIKELY TO RAIN, BUT WOULDN'T BET ON IT. NO R A I N L A S T NIGHT S O WE DON'T KNOW I F THE W3P WOULD HAVE STAYED DOWN OR NOT. THE MACHINE WORKED OK AND HAD SOME F I V E HUNDRED RECORDINGS. A L S O NOTE; WE S T A R T E D T H E R E T R I E V E AND THEN UNPLUGGED THE MAT AND LOOPS-THIS APPARENTLY I S NOT SUPPOSED TO BE DONE BECAUSE E I T H E R THE RETRIEVER OR THE WEIGHMAN LOCKED-UP AND AFTER ABOUT 7 MINUTES HAD TO PUSH CANCEL AND START OVER. LUCKILY WE D I D N ' T LOSE THE DATA. THEN THERE APPEARED ONE ERROR I N STATUS MODE 1. SCANNING THE DATA SHOWS AN ABUNDANCE O F SLOWER TRUCKS, WE F I G U R E I T ' S BECAUSE T H I S LOCATION I S SLIGHTLY U P - H I L L AND NOT TOO FAR FROM THE 1-40 T . I . WE ALSO NEED NEW UNDER PADS. T H I S MORNING THE PAD HAD MIGRATED FROM UNDER THE MAT ON THE DOWNSTREAM S I D E . I T WAS S T I L L WET UNDERNEATH ALSO. HOPEFULLY T H I S I S THE LAST TIME WE HAVE TO S E T 1-17 SOUTH O F FLAG. FORENSIC.030 88/09/15 15:OO:OO FORENSIC WIM STUDY SITE 30 NORTH OF FLAGSTAFF ON US-89 AT MP 434.23 NB SET ON SPEED LOOPS 18' LEADING EDGE TO LEADING EDGE. MACHINE 0381-0014 MAT 157 OSC 4 SLIGHT DOWN HILL AT END OF LONG DOWN HILL FROM SADDLE. SITE #00143001 SINGLE LANE SB SET ON TEMP LOOPS 18' LEADING EDGE TO LEADING EDGE. MACHINE 0349-0003 MAT 207 OSC 1 SLIGHT UPHILL AT BOTTOM OF LONG UPHILL TO SADDLE. SITE # 00033002 LOOPS PUT DOWN WITH PRIMER & SCOTCH RUBBER TAPE. TWO LANES SET IN SLOW LANE. SB NO COMMUNICATION. BATTERY IS NB RETRIEVED TO FORENSIC.30A. 5.6 VOLTS ON VOM. NO RETRIEVE. NO MORE BATTERIES, WAITING FOR TEMPERATURE/VOLTAGE TO COME UP AND SEE WHAT HAPPENED. SB RETRIEVED TO FORENSIC.30B WITH DIFFICULTY. BATTERY READOUT IS 5.3 VOLTS. VOM SHOWS BATTERIES AT 5.6V. MACHINE IS 23: 30 RESET TO CURRENT TIME & DATE. FAILED. RESET RECORDINGS, "01', BECAUSE STATUS MODE 2 HAD u--- " DISPLAY. LOST COMMUNICATIONS. RETRIEVER HAS UNCHANGED TIME DATE & RECORDINGS, "116". RESET FAILED. SB RESET FAILED. BATTERIES SHOW 5.62V ON VOM. SB RESET FAILED. BATTERIES SHOW 5.64V ON VOM. NB CHECKED. ON VOM. .. 56 VEHICLES. SB RESET FAILED. BATTERIES SHOW 5.67V SB RESET FAILED. BATTERIES SHOW 5.68V ON VOM. SB RESET FAILED. BATTERIES SHOW 5.69V ON VOM. SF3 RESET FAILED. I QUIT WITH THIS MACHINE. NB RETRIEVED TO FORENSIC.30C END NB. SB SETUP WITH 0381-0014 ON MAT 157 SITE #00143002 ALL ELSE SAME. START SB AT 14:40 BELOW FREEZING AGAIN LAST NIGHT. SB RETRIEVED TO FORENSIC.30D WORKING FINE. M O P S ARE LOOKING GOOD. SB CHECKED OK. SB RETRIEVED TO FORENSIC.30E END SB. DOWN NICELY. END SITE BOTH LX)OPS ON SB STAYED