The passenger flow of urban rail transit (UTR) is influenced by many factors including gross domestic production, total length of urban rail lines, and the urban population scale of the city. A macro-factor passenger flow estimation model is needed for more and more cities in Chinato to build urban rail transit system. Before the urban rail transit becomes an operating network, a lot of government agencies usually build the first metro line in the center of city. Considering only one line services a limited number of people in the city, a modified multiple variables linear regression model is established based on the URT operating data in cities of China which can forecast the passenger flow of urban rail transit exactly. The results show that the model is very accurate in passenger flow forecasting.


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    Title :

    Modification of Macro-Factor Passenger Flow Forecasting Model of Urban Rail Transit


    Contributors:
    Shang, Bin (author) / Sun, Qiang (author) / Qu, Limin (author)

    Conference:

    15th COTA International Conference of Transportation Professionals ; 2015 ; Beijing, China


    Published in:

    CICTP 2015 ; 1292-1299


    Publication date :

    2015-07-13




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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