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Using Truck GPS Data for Freight Performance Analysis in the Twin Cities Metro Area

Chen-Fu Liao-2014-03-01-University of Minnesota Digital Conservancy (University of Minnesota)
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TL;DRAbstract

Building on our previous efforts to study freight mobility and reliability, a GPS-based data analysis methodology was developed to study the freight performance of heavy commercial trucks along 38 key freight corridors in the Twin Cities metropolitan area (TCMA). One year of truck GPS data collected in 2012 was obtained from American Transportation Research Institute (ATRI) to study freight mobility and reliability. Several performance measures, such as truck mobility, delay, and reliability index, were computed and analyzed by route, roadway segment, and time of day. For data quality and reliability verification, average truck speed and hourly volume percentage computed from the truck GPS data were validated with weigh-in-motion (WIM) and automatic traffic recorders (ATR) data at selected locations. The GPS based freight analysis methodology offers potential opportunities for freight planners and managers to generate reliable measures in a timely manner. The resulting performance meas

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Building on our previous efforts to study freight mobility and reliability, a GPS-based data analysis methodology was developed to study the freight performance of heavy commercial trucks along 38 key freight corridors in the Twin Cities metropolitan area (TCMA). One year of truck GPS data collected in 2012 was obtained from American Transportation Research Institute (ATRI) to study freight mobility and reliability. Several performance measures, such as truck mobility, delay, and reliability index, were computed and analyzed by route, roadway segment, and time of day. For data quality and reliability verification, average truck speed and hourly volume percentage computed from the truck GPS data were validated with weigh-in-motion (WIM) and automatic traffic recorders (ATR) data at selected locations. The GPS based freight analysis methodology offers potential opportunities for freight planners and managers to generate reliable measures in a timely manner. The resulting performance meas

Keywords

Twin citiesGlobal Positioning SystemTruckTransport engineeringComputer scienceGeographyMetropolitan areaEngineering

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