Collection and Analysis of Augmented Weigh-in-Motion Data

009280631996PDFTech ReportTX-99/987-8Traffic dataPavement designWeigh in motionCost effectivenessTraffic loadsTraffic volumeRigid pavementsFlexible pavementsEquivalent single axle loads (ESALs)Lufkin DistrictOverlay strategiesPavement damagePavement rehabilitationTrendsUS 59TexasUnited StatesUniversity of Texas at Austin. Center for Transportation ResearchLee, Clyde E.Garner, Joseph E.University of Texas at Austin. Center for Transportation ResearchTexas. Dept. of TransportationBTS Data DirectoryTraffic loading data are essential for the planning and design of adequate and cost-effective highway pavements. Data from an augmented weigh-in-motion (WIM) system have been collected and analyzed. The augmented WIM systems, which comprise bending-plate weighpads, infrared sensors, inductance loop detectors, and thermocouples, were installed in the southbound lanes of Highway 59 in east Texas in 1992. Data have been collected continuously since December 1992 for each vehicle and include date, time, lane, speed, number of axles, axle spacing, and wheel loads. The infrared sensors measure the lateral position of vehicle tires in the traffic lane and indicate single or dual tires. Hourly pavement and air temperatures are recorded by the thermocouples. While some preliminary data analysis is done on-site by the WIM-system computer, an Excel spreadsheet macro computer program was written for further data analysis, including vehicle classification and calculation of equivalent single axle loads (ESALs), a common way of expressing traffic loading. Some data trends have been analyzed, including the proportion of various vehicle classes and lane use. Periodic trends by day of the week and month of the year have also been examined. A methodology is outlined and illustrated for using traffic-volume and vehicle-class data, which are more commonly available than axle-load data, to estimate ESALs. The average ESAL factor per axle group of a given vehicle class is used to convert vehicles per day to ESALs per day. The cumulative ESALs at a site depend on the traffic volume and axle loads and may vary by the day of the week and season of the year. A growth-rate factor may be applied to forecast ESAL totals for future periods of time. Total predicted ESALs are used in the design and analysis of pavement structures.85