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WIM Data Analysts Manual
Publication No. FHWA-IF-10-018
Table of Contents
- SECTION 1. INTRODUCTION
- 1.1. OVERVIEW OF WIM
- 1.2. SIGNIFICANCE OF HIGH QUALITY WIM DATA
- 1.3. OVERVIEW OF THE MANUAL
- SECTION 2. WIM BASICS
- 2.1. WIM SYSTEM VS. WIM SITE
- 2.2. DEFINITIONS AND TERMS
- 2.3. VEHICLE CLASSIFICATION VERSUS VEHICLE TYPE
- 2.4. TASKS OF THE OFFICE DATA ANALYST
- 2.4.1. Causes of Missing or Invalid Data
- 2.4.2. Factors Affecting WIM Data Quality Which Can Be Controlled
- 2.4.3. Factors Affecting WIM Data Quality Which Can Be Somewhat Controlled (By Site Selection)
- 2.4.4. Factors Affecting WIM Data Quality Which Cannot Be Controlled
- 2.5. WHAT QUALITY OF DATA SHOULD BE EXPECTED?
- SECTION 3. STEPS FOR DATA VALIDATION AND SYSTEM MONITORING FROM OFFICE
- 3.1. INITIAL REAL-TIME REVIEW
- 3.2. DATA REVIEW USING CANNED REPORTS
- 3.2.1. Class and Speed Reports
- 3.2.2. Individual Vehicle Record Summary Reports
- 3.3. AUTOMATED VALIDATION PROGRAMS
- 3.4. DATA QC - FOLLOW-UP PROCEDURES
- 3.4.1. Real-Time System Check of Parameters and Settings
- 3.4.2. Remote Real-Time Tests and Diagnostics of System Component Operation
- SECTION 4. EXTENSIVE DATA ANALYSES UTILIZING INDIVIDUAL VEHICLE RECORDS
- SECTION 5. STEPS FOR MONITORING SYSTEM CALIBRATION FROM OFFICE
- 5.1. GENERATE WEIGHT AND AXLE SPACING STATISTICS FOR SAMPLE OF TRUCK TRAFFIC STREAM
- 5.2. MONITORING TRUCK TRAFFIC STREAM STATISTICS OVER TIME
- 5.3. EFFECTS OF CALIBRATION FACTOR ADJUSTMENTS ON TRUCK TRAFFIC STREAM DATA
- 5.4. ADJUSTMENT OF CALIBRATION FACTORS BASED UPON TRUCK TRAFFIC STREAM DATA
- 5.5. RESOLVING ACCURACY PROBLEMS IDENTIFIED BY MONITORING OF TRUCK TRAFFIC STREAM
- 5.5.1. Gross Weight Distribution
- 5.5.2. Individual Sensor Weight Outputs
- 5.5.3. Axle Spacings (and thereby speed)
- 5.5.4. Overall Vehicle Length
- 5.6. MAKING BEST USE OF AVAILABLE RESOURCES
- SECTION 6. REFERENCES
- APPENDIX A
- APPENDIX B
- APPENDIX C
List of figures
- Figure 1. List. ASTM E 1318 Type I WIM Systems Requirements
- Figure 2. Photo. Staggered weigh sensors (bending plates) and detection loops (single threshold system).
- Figure 3. Photo. In-line weigh sensors (single load cells), a trailing axle sensor, and detection loops (single threshold system)
- Figure 4. Photo. In-line weigh sensors (quartz piezos) and detection loops (double threshold system).
- Figure 5. Photo. Controller cabinet, front view
- Figure 6. Photo. Controller cabinet, rear view, with in-road sensor inputs to controller and lightning protection.
- Figure 7. Photo. Two-lane WIM site, with Portland cement concrete (PCC) pavement installed for approach and departure
- Figure 8. Photo. Class 7, single-unit truck with four of its five axles in contact with pavement.
- Figure 9. Photo. Class 8, Type 2S1
- Figure 10. Photo. Class 8, Type 3S1
- Figure 11. Photo. Class 9, Type 3S2
- Figure 12. Photo. Class 9, Type 3S2 with "spread" rear tandem
- Figure 13. Photo. Class 9, Type 32
- Figure 14. Photo. Class 10, Type 3S3
- Figure 15. Photo. Class 11, Type 2S12
- Figure 16. Photo. Class 12, Type 3S12
- Figure 17. Picture. Class 13, Longer Combination Vehicles (LCVs)
- Figure 18. Screen shot. Site menu, time and date
- Figure 19. Screen shot. Site menu, stored data files
- Figure 20. Screen shot. Site real-time "View Vehicles" mode for system's Lane 1
- Figure 21. Screen shots. Menu screen displaying portion of classification algorithm entries
- Figure 22. Screen shot. Site real-time "View Vehicles" mode
- Figure 23. Screen shots. Site real-time menu screen displaying calibration factors
- Figure 24. Reports. Missing hourly data for lane or lanes
- Figure 25. Report. Missing data all lanes
- Figure 26. Report. Erroneous classification for lane
- Figure 27. Report. Erroneous speeds for lane
- Figure 28. Report. Speed by class for lane
- Figure 29. Report. Class and speed distributions, Lane 1 versus Lane 2
- Figure 30. Report. Traffic congestion; legitimate low speeds
- Figure 31. Report. Change in class count pattern and increase in system errors for lane
- Figure 32. Report. System error identification
- Figure 33. Report. Individual vehicle record class and weight summary data for one lane
- Figure 34. Screenshots. Examples of vehicles not classified by the system
- Figure 35. Screen shots. Legitimate Class 13 vehicles
- Figure 36. Screen shot. Vehicle misclassified as Class 13 due to "ghost" axles
- Figure 37. Screen shot. Two records for one combination vehicle
- Figure 38. Photo. Class 9 Type 32 with long towbar
- Figure 39. Photo. Class 9 logging truck
- Figure 40. Report. Class distribution, weight violation counts, and warning counts by lane
- Figure 41. Report. Error and warning vehicles by hour for lane
- Figure 42. Screen shot. Vehicle with "light" wheel weights on left side
- Figure 43. Report. Gross weight distribution for each truck class for lane
- Figure 44. List. Summary of FHWA TMAS QC Checks
- Figure 45. Screen shot. Example of a record of a system's setup parameters for one lane
- Figure 46. Screen shot. Example of a record of a system's weight calibration factors for one lane.
- Figure 47. Screen shot. Example of a system's sensor configuration and loop delay constant for one lane.
- Figure 48. Screen shots. Example of a system's menu screen for selecting system tests ("System test") and three examples of the tests
- Figure 49. Screen shot. Example of a system's loop and weigh sensor duration diagnostics
- Figure 50. Screen shot. Example of system's menu page displaying a bending plate sensor's baseline value.
- Figure 51. Screen shot. Portion of simple spreadsheet filtered for unclassified vehicles
- Figure 52. Screen shot. Plot of Class 9 steer axle wheel weights by hour of day
- Figure 53. Screen shot. AX1LT sorted for ascending values
- Figure 54. Screen shot. AX1RT sorted for ascending values
- Figure 55. Photo. Class 9, Type 3S2 typical axle and wheel alignment crossing right and left weigh sensors.
- Figure 56. Screen shot. Calculated fields for testing "Invalid Measurement" flags and analyzing axle imbalances
- Figure 57. Screen shot. Invalid Measurement weights by GVW range
- Figure 58. Screen shot. Table displaying summary of axle right versus left weight imbalance statistics.
- Figure 59. Photo. This vehicle combination may conform to a Class 9 Type 2S3 under some classification schemes
- Figure 60. Tabular Report. Distribution of lane counts by GVW, for site with mix of both loaded and empty Class 9 vehicles
- Figure 61. Report Graph. Distribution of lane counts by GVW, for site with mix of both loaded and empty Class 9 vehicles
- Figure 62. Tabular Report. Distribution of lane counts by GVW, site with very few empty Class 9 vehicles.
- Figure 63. Report Graph. Distribution of lane counts by GVW, site with very few empty Class 9 vehicles.
- Figure 64. Procedure. Pre calibration - right and left sensor balance
- Figure 65. Report. Distribution of Class 9 weights and axle spacings by speed for one lane, flat roadway grade.
- Figure 66. Report. Distribution of Class 9 weights and axle spacings by speed for one lane, uphill grade.
- Figure 67. Report. Distribution of Class 11 weights, vehicle length, and wheelbase by speed for one lane.
- Figure 68. Screen shot. "Tables" Worksheet
- Figure 69. Screen shot. Weight statistics for calibration monitoring and tracking
- Figure 70. Screen shot. Additional statistics for calibration monitoring and tracking
- Figure 71. Screen shot. GVW distribution plot
- Figure 72. Screen shot. Weights versus speed statistics
- Figure 73. Graph. Traffic stream Class 9 GVW distribution plots for 12 consecutive months, long haul high volume
- Figure 74. Graph. Traffic stream Class 9 Axle 1 weight distribution plots for 12 consecutive months.
- Figure 75. Graph. Class 9 GVW distribution plots for spring season over three-year period, local traffic.
- Figure 76. Graph. GVW distribution plots for 12 consecutive months, low volume
- Figure 77. Graph. Class 9 GVW distribution plots for 12 consecutive months, weight shift
- Figure 78. Graphs. Calibration test truck GVW WIM error versus speed plots, and truck traffic stream speeds versus calibration test truck speeds plots
- Figure 79. Graph. Class 9 traffic stream GVW distribution plots before and after calibration factor adjustments.
- Figure 80. Graph. Class 9 traffic stream GVW distribution plots over period with no calibration factor changes.
- Figure 81. Graph. Calibration test truck GVW WIM error versus speed plots
- Figure 82. Graph. Calibration test truck GVW WIM error x speed plots, before and after factor adjustments.
- Figure 83. Graph. Effects of calibration factor adjustments on traffic stream WIM weights
- Figure 84. Screen shot. Tracking of system modifications and monthly calibration monitoring statistics.
- Figure 85. Graph. Class 9 GVW distribution plots, empty and loaded peaks too heavy
- Figure 86. Graphs. Calibration test truck GVW WIM error x speed plots and truck traffic stream speeds versus calibration test truck speeds plots, ineffective calibration
- Figure 87. Screen shot. Weights versus speed statistics, ineffective calibration
- Figure 88. Procedure. Procedures and examples for adjusting calibration factors based upon traffic stream data statistics
- Figure 89. Procedure. Procedure and example for adjusting axle spacing lengths (and thereby speeds)
- Figure 90. Procedure. Procedure and example for adjusting overall vehicle lengths
List of tables
- Table 1. Example Class Scheme
SI Conversion Factors
This manual provides information and recommended procedures to be utilized by an agency's Weigh-in-Motion (WIM) Office Data Analyst to perform validation and quality control (QC) checks of WIM traffic data. This manual focuses on data generated by WIM systems that have the capability to produce high quality data. Many of the recommended data QC procedures are dependent upon data containing wheel loads (in conformance with the Type I WIM system requirements of ASTM E 1318). However, the more basic QC procedures discussed may be of use to an analyst performing checks on data generated by systems generating only axle load data (conforming to Type II system requirements of ASTM E 1318) and/or systems relying upon autocalibration features deemed necessary to obtain loading data adequate for certain programs.
This document is intended to present the WIM data analysts with the necessary information and guidance to identify missing or invalid WIM data, to determine the cause and extent of missing or invalid data, and the course of action to correct problems. Basic information and recommendations are provided for the novice analyst, and more extensive procedures and guidelines are provided to develop and assist experienced analysts.
To follow the procedures recommended in this manual will take a great deal of time and effort by the data analyst. However, the proper installation and maintenance of high quality WIM systems is a costly investment. Such investment provides an agency only with the capability to obtain high quality traffic data. Such high quality data will not be achievable in the absence of following diligent data QC and system monitoring procedures.
This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.
The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.
Quality Assurance Statement
The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.
Technical Report Documentation Page
|1. Report No. |
|2. Government Accession No.||3. Recipient's Catalog No.|
|4. Title and Subtitle |
WIM Data Analyst's Manual
|5. Report Date |
|6. Performing Organization Code: |
|7. Author(s) |
|8. Performing Organization Report No.|
|9. Performing Organization Name and Address |
The Transtec Group
6111 Balcones Drive
Austin, TX 78731
|10. Work Unit No.|
|11. Contract or Grant No. |
|12. Sponsoring Agency Name and Address |
FHWA Office of Pavement Technology
1200 New Jersey Ave. SE
Washington, DC 20590
|13. Type of Report and Period Covered |
|14. Sponsoring Agency Code |
|15. Supplementary Notes |
FHWA Contracting Officer's Technical Representative (COTR): Mike Moravec
|16. Abstract |
This manual provides information and recommended procedures to be utilized by an agency's Weigh-in-Motion (WIM) Office Data Analyst to perform validation and quality control (QC) checks of WIM traffic data. This manual focuses on data generated by WIM systems that have the capability to produce high quality data. Many of the recommended data QC procedures are dependent upon data containing wheel loads (in conformance with the Type I WIM system requirements of ASTM E 1318). This manual has been developed to ensure that high quality WIM data is collected and used to produce reliable and representative load spectra for input into the Mechanistic-Empirical Pavement Design Guide (M-E PDG) software resulting in reliable and predictable pavement designs. While this is the primary use, there are many other uses including performing checks on data generated by systems that produce only axle load data.
|17. Key Words |
WIM Data Analysis, WIM Data Validation, WIM Data Quality Control, Traffic Inputs for Pavement Design, M-E PDG, and Load spectra
|18. Distribution Statement |
No restrictions. This document is available to the public through the Federal Highway Administration (FHWA)
|19. Security Classif. (of this report) |
|20. Security Classif. (of this page) |
|21. No. of Pages|
|22. Price |
|Form DOT F 1700.7 (8-72) Reproduction of completed page authorized||