Highlights Propose general and objective approaches for determining key threshold parameters. Propose a data-driven approach to measure the circuitous degree of truck trajectories. Propose a temporary stop elimination method by using auxiliary data. Analyze the potential applications of intracity freight trips of heavy trucks.

    Abstract Intracity heavy truck freight trips are basic data in city freight system planning and management. In the big data era, massive heavy truck GPS trajectories can be acquired cost effectively in real-time. Identifying freight trip ends (origins and destinations) from heavy truck GPS trajectories is an outstanding problem. Although previous studies proposed a variety of trip end identification methods from different perspectives, these studies subjectively defined key threshold parameters and ignored the complex intracity heavy truck travel characteristics. Here, we propose a data-driven trip end identification method in which the speed threshold for identifying truck stops and the multilevel time thresholds for distinguishing temporary stops and freight trip ends are objectively defined. Moreover, an appropriate time threshold level is dynamically selected by considering the intracity activity patterns of heavy trucks. Furthermore, we use urban road networks and Point-of-Interest (POI) data to eliminate long-stay temporary stops to improve method accuracy. The validation results show that the accuracy of the method we propose is 88.79%. Our method incorporates the impact of the city freight context on truck trajectory characteristics, and its results can reflect the spatial distribution and chain patterns of intracity heavy truck freight trips, which have a wide range of practical applications.


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    Titel :

    Identifying intracity freight trip ends from heavy truck GPS trajectories


    Beteiligte:
    Yang, Yitao (Autor:in) / Jia, Bin (Autor:in) / Yan, Xiao-Yong (Autor:in) / Jiang, Rui (Autor:in) / Ji, Hao (Autor:in) / Gao, Ziyou (Autor:in)


    Erscheinungsdatum :

    2022-01-13




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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