Freight road vehicle operations vary widely depending on a multitude of factors such as industry type, commodities transported or geographical scope. Vehicle tracking is one of the most common approaches to understand operation patterns and it has been facilitated by the increasing availability of GPS-enabled devices. We describe a method that supplements vehicle tracking data with day-to-day driver activity surveys to collect static and dynamic data related to freight vehicle operations. The survey was designed to enable innovative data analysis and modelling. We detail the data collection method demonstrated in Singapore and illustrate three data-driven insights which are of interest in the urban freight domain: (1) freight vehicle overnight parking, (2) tour patterns and associated vehicle usage characteristics, and (3) commodity flow patterns. The unique insights demonstrated by the analyses corroborate the potential of the described data collection method to further understand freight vehicle operations.


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    Titel :

    Next-generation freight vehicle surveys: Supplementing truck GPS tracking with a driver activity survey


    Beteiligte:
    Alho, Andre Romano (Autor:in) / You, Linlin (Autor:in) / Lu, Fangping (Autor:in) / Cheah, Lynette (Autor:in) / Zhao, Fang (Autor:in) / Ben-Akiva, Moshe (Autor:in)


    Erscheinungsdatum :

    01.11.2018


    Format / Umfang :

    594321 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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