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

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

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Minnesota Department of Transportation Research Services & Library




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 measures indicate that these measures derived from truck GPS data can be used to support the USDOT performance measure initiative and support regional surface freight planner in identifying freight bottlenecks, infrastructure improvement needs, and operational strategies to promote efficient freight movement. FHWA recently announced the National Performance Measurement Research Data Set (NPMRDS) to support its Freight Performance Measurement (FPM). The NPMRDS includes probe vehicle based travel time data in every 5-minute interval. This report also explored the feasibility of using one month of NPMRDS data in Minnesota to compute freight mobility and speed variations along the National Highway System (NHS) during AM and PM peak periods.


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Department of Civil Engineering University of Minnesota

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Chen-Fu, Liao. (2014). Using Truck GPS Data for Freight Performance Analysis in the Twin Cities Metro Area. Retrieved from the University Digital Conservancy,

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