Demand-responsive customized bus (DRCB) is a specific type of demand-responsive transit (DRT), which can flexibly customize services according to travel demand. However, few papers explored the influence factors on it. The purpose of this paper is to use the DRCB trip data from November 15 to December 15, 2020, in Xiongan New Area, China, to investigate the influence of built environment, weather, and time factors on DRCB ridership by using a negative binomial regression model. According to the spatiotemporal analysis, DRCB ridership is mainly concentrated in the peak hours of 07:00-09:00 and 17:00-20:00; the spatial distribution is primarily centered in areas such as government service center, railway station, and residential area. The model results show that scenic spot, governmental agency, morning peak period, and evening peak period are positively correlated with the DRCB ridership. Company, medical facility, visibility, rain, and weekend have a negative correlation with DRCB ridership. The results of this paper can provide insights for relevant companies to better understand the demand for DRCB and better plan the DRCB systems.


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    Titel :

    Exploring the influencing factors on demand-responsive customized bus ridership using multi-source data


    Beteiligte:
    Huo, Yamin (Autor:in) / Qiu, Zhongquan (Autor:in) / Xin, Yi (Autor:in) / Dai, Shideng (Autor:in) / Pan, Renbin (Autor:in) / Wen, Yi (Autor:in)


    Erscheinungsdatum :

    2021-10-22


    Format / Umfang :

    3074859 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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