The relationship between taxi travel patterns and public transportation disruption has not been extensively explored. In this study, we investigated the impact of public transportation disruption on the taxi mobility patterns during the metro shutdown in Washington, D.C.. Multiple data source, involving taxi trips, traffic analysis zone, and point of interest (POI) information, was collected to compare the taxi travel patterns before, during, and after the metro shutdown. The number, distance, and duration of taxi trips were found to be significantly higher during the metro shutdown; specifically, the number of taxi trips was found to be 19.8% larger. Furthermore, a POI auxiliary analysis was performed to investigate the variation in community structure during the disruption of public transport using the modularity maximization approach. The results of this study will be useful for the development of taxi scheduling strategies and traffic management.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Uncovering Taxi Mobility Patterns Associated with the Public Transportation Shutdown Using Multisource Data in Washington, D.C.


    Weitere Titelangaben:

    KSCE J Civ Eng


    Beteiligte:
    Jia, Jianmin (Autor:in) / Zhang, Hui (Autor:in) / Shi, Baiying (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2022-12-01


    Format / Umfang :

    10 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Uncovering the spatially heterogeneous effects of shared mobility on public transit and taxi

    Tang, Jinjun / Gao, Fan / Han, Chunyang et al. | Elsevier | 2021



    Establishing Multisource Data-Integration Framework for Transportation Data Analytics

    Cui, Zhiyong / Henrickson, Kristian / Biancardo, Salvatore Antonio et al. | ASCE | 2020



    Revealing Urban Community Structures by Fusing Multisource Transportation Data

    Ding, Shuo / Zhang, Michael / Xing, Yingying et al. | ASCE | 2022