Heavy rainfall, as a kind of adverse weather condition, can have an extremely negative impact on subway ridership. This paper proposed a comprehensive framework to analyze the rainfall impact on subway transit ridership. Firstly, rainfall events were detected from the precipitation data. Then, heterogeneous characteristics of subway transit trips, such as the trip duration, the functionality of subway stations, and the trip elasticity, were extracted from smart card data. Finally, ridership fluctuation coefficient was calculated to measure the rainfall-induced ridership fluctuation degree quantitatively. It figured out that heavy rainstorm could cause as much as forty percent of reduction on ridership. Meanwhile, different kinds of trips showed different levels of sensitivity to rainfall. Long or elastic trips were more vulnerable, and trips flowing to airports or tourist spots could be sharply cut down by rainfall events. The research results can help metro operators improve their service quality under certain forecasted weather conditions.


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    Titel :

    Impact Analysis of Rainfall on Beijing Subway Transit Ridership with Heterogeneous Characteristics


    Beteiligte:
    Tang, He (Autor:in) / Zhang, Yong (Autor:in) / Liu, Hao (Autor:in) / Kong, Dehui (Autor:in) / Ge, Yun (Autor:in)

    Kongress:

    17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China


    Erschienen in:

    CICTP 2017 ; 236-247


    Erscheinungsdatum :

    18.01.2018




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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