Expanding the Uses of Truck GPS Data in Transportation Planning and Analysis
Corresponding Author: Shuyao Hong, Maricopa Association of Governments
Presented By: Shuyao Hong, Maricopa Association of Governments
Abstract
Big Data sources that became available in the past few years, especially truck GPS data from commercial data sources, formed strong foundations for the freight modeling and regional truck movement forecasts. In the development and maintenance of truck models, the most common uses of Truck GPS data are the extraction of trip matrices and estimation of tour models. As GPS data contain a large amount of spatial-temporal information, in order to get the most out of it, additional data mining and visual analytics applications are needed to transform data into meaningful insights about truck activities.
As one of SHRP2 C20 Freight Model grant recipients, Maricopa Association of Governments (MAG) have acquired GPS data for light, medium, and heavy duty trucks from third-party data providers – American Transportation Research Institute (ATRI) and StreetLight Data, Inc. – to facilitate the development of tour-based behavioral truck models. Beyond the standard trip matrices extraction and tour model estimation, MAG analyzed the GPS data in various ways to benefit transportation planning, freight study, and traffic study, including validation between GPS sample and vehicle classification counts, truck tour characteristic analysis, truck trajectories reconstruction on the network using an innovative map matching algorithm, and visualizing the truck movement and route choice patterns.
This presentation will mainly focus on (1) an overview of sample data characteristics, (2) a brief discussion of GPS data processing, and (3) showcase of truck GPS data analysis and visual analytics applications for transportation planning and analysis.