As high-speed railways become more accessible in China, it is significant to clarify the travel characteristics of different station types to facilitate their planning and construction. Based on travel data from Baidu Map, this paper studies two railway hubs in Nanjing as examples. The trip distribution models were established using ordinary and spatial regression methods, respectively. Based on the principle of gravity model, the trip distribution models incorporating land use factors were established. The geographically weighted regression method was applied to form local models, which significantly improves the fitting effect in the scenarios of Nanjingnan Railway Station. The research shows that land use types, including residential, transportation, and green space, show a positive correlation with travel volumes in traffic zones, and different degrees of spatial heterogeneity were observed. The research completes the influencing factors of trip distribution of railway stations, reveals the differences related to station types, and improves the fitting effect generally.


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    Titel :

    Trip Distribution Characteristics of Railway Hubs Established from OD Data: A Case Study in Nanjing, China


    Beteiligte:
    Gao, Haowen (Autor:in) / Li, Wenquan (Autor:in) / Wang, Wei (Autor:in)

    Kongress:

    24th COTA International Conference of Transportation Professionals ; 2024 ; Shenzhen, China


    Erschienen in:

    CICTP 2024 ; 3513-3523


    Erscheinungsdatum :

    11.12.2024




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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