EXPANDING TRUCK GPS-BASED PASSIVE ORIGIN-DESTINATION DATA IN IOWA AND TENNESSEE

The availability of large samples of truck global positioning system (GPS) data has presented a new, unprecedented source of information for understanding truck travel patterns and forecasting truck demand. This data is now being incorporated in the development of statewide models, beginning with Indiana’s in 2012 and now with Iowa and Tennessee’s. In order to use the data in modeling and forecasting, it is necessary to expand the GPS-based sample data to represent all truck movements. This presents a challenge, since the sample is not randomly drawn and cannot therefore be presumed to be representative. In particular, this paper presents confirmation that short-haul movements, while present in the data, are under-represented. Without correcting for this, it is not possible to produce accurate information regarding average trip lengths, etc., or to accurately forecast future truck activity. This paper presents on-going work to understand the representativeness of the American Transportation Research Institute’s (ATRI) truck GPS data and develop methodologies to produce factors for expanding it to ensure it is representative of truck travel patterns in general.