In the trend of rapid urbanization, public transportation plays a vital role in the sustainable development of transportation systems. As one of the most important public transportation modes, urban rail transit (URT) is the key solution of a series of metropolitan traffic problems, and is being constructed with rapid speed in China. However, it is very difficult for decision makers to quantify and evaluate the scale of the urban rail transit network (URTN). In this paper, the length of the URTN is selected to measure the scale of the URTN. Two regression models, including one linear and one nonlinear, are constructed to predict the length of the URTN based on a database with a sample size of forty from sixteen Chinese cities. Finally, a case is proposed to validate the feasibility of the models. The results show that downtown population size, downtown population density, and urban gross domestic product (urban GDP) positively influence the length of URTN. Furthermore, it reveals that nonlinear regression model is slightly better than the linear one in terms of fitting degree. This study would contribute to providing important references to establish and implement URT development policies.


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    Titel :

    Prediction Model of Chinese Urban Rail Transit Network Scale


    Beteiligte:
    Han, Jingwei (Autor:in) / Yan, Xuedong (Autor:in) / Ma, Lu (Autor:in) / Li, Xiaomeng (Autor:in)

    Kongress:

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


    Erschienen in:

    CICTP 2015 ; 3776-3787


    Erscheinungsdatum :

    13.07.2015




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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