With the increasing installations of GPS devices on trucks, massive GPS data provide the possibility of extracting daily trips with detailed and comprehensive information. A framework for truck OD estimation is proposed and tested in a truck traveling analysis in Liaoning Province. Emphasis trips are classified into two categories depending on highway usage, and four key indicators with the corresponding haul distance distribution are compared with travel survey data for validation. Meanwhile, trips with short-haul distances are classified into yard and road trips, where the latter category can help estimate road maintenance with load information in the future study. Results show that the haul distribution and the key indicators are relatively the same with the corresponding values of the survey data. Thus, GPS data could be used to describe the freight features in Liaoning Province.


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    Title :

    Mining Massive Truck GPS Data for Freight OD Estimation: Case Study of Liaoning Province in China


    Contributors:
    Huo, Enze (author) / Zhang, Peng (author) / Li, Honghai (author) / Wang, Yingping (author) / Luan, Sen (author) / Ma, Xiaolei (author)

    Conference:

    20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)


    Published in:

    CICTP 2020 ; 86-98


    Publication date :

    2020-08-12




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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