ANALYSIS OF WEIGH-IN-MOTION TRUCK TRAFFIC DATA TO DETERMINE TRUCK DAMAGE FACTORS AND AVERAGE WEIGHTS

The Florida Department of Transportation (FDOT) Weigh-in-Motion (WIM) truck traffic data were analyzed to generate average truck damage factors and average weight for each truck classification. Visual Basic and the statistical package in Excel were used to calculate the number of trucks, maximum, minimum and average damage factors and average weight for each type of truck. The trucks were classified according to the FDOT's standard classification system. Seven classes of trucks were analyzed at nine sites in the State of Florida. The 18-kip Equivalent Single Axle Load (ESAL) or load equivalency is used to calculate damage factors for each type of truck. The American Association of State Highway and Transportation Officials (AASHTO) test results show that roadway damage caused by trucks increases approximately in accordance with the load in ESALs multiplied to the fourth power. This concept is used in the calculation of damage factors. Each WIM data file was sorted and the bad data (the data that did not meet the established criteria) were excluded from the analysis. A computer program was developed in which established criteria tables sorted out the data according to the vehicle classifications of loaded and unloaded. Modules were formed to include different functional macros. Bar charts were prepared showing the total number of each truck classification, average loaded damage factors and total damage factors. Furthermore, prepared charts show the site number, the total records of data in a WIM file, the percentages of total good data (the data that meet the criteria) and bad data, truck type, and percentages of loaded and unloaded trucks. The charts also present the average, maximum and minimum damage factors and the standard deviations for both loaded and unloaded trucks. The generated results are useful to planners and highway designers. The main objectives of this research project were to develop systematic procedures for the collection and analysis of WIM data and to identify the parameters and influencing factors that affect damage factor and average weight calculations. Statistical models are developed to set up a hypothesis to determine if the means of the total average truck weights are equal in all sites under the study.

• Corporate Authors:

  University of Florida, Gainesville

  Department of Civil Engineering, P.O. Box 116580
  Gainesville, FL  United States  32611-6580

  Florida Department of Transportation

  Haydon Burns Building, 605 Suwanee Street
  Tallahassee, FL  United States  32301

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Najafi, F T
  • Yao, Q-Y
  • Blackadar, B
  • Lee, Jong Jae
  • Ruiz, D M
  • Ferraro, C C
• Publication Date: 1997-5

Language

• English

Media Info

• Features: Appendices; Figures; References; Tables;
• Pagination: 87 p.

Subject/Index Terms

• TRT Terms: Axle load force; Data analysis; Equivalent single axle loads; Mathematical analysis; Traffic equivalence factor; Trucks; Trucks by weight; Weigh in motion; Weight
• Geographic Terms: Florida
• Old TRIS Terms: Truck pavement damage
• Subject Areas: Highways; Motor Carriers; Operations and Traffic Management; I71: Traffic Theory;

Filing Info

• Accession Number: 00738019
• Record Type: Publication
• Report/Paper Numbers: WPI 0510733, Final Report, UF Proj 4910450452512,, FDOT Proj 99700-3307-010
• Contract Numbers: B-9918
• Files: TRIS, USDOT, STATEDOT
• Created Date: Jun 27 1997 12:00AM