This paper builds a two-stage model to predict the Urban Rail Transit (URT) share rate of the cities with no rail presently. The first stage will predict the proportion of the transport structure with no rail using transfer curve. At the second stage, some influencing factors are selected as characteristic variables of the utility function to forecast passengers transferring from other traffic modes to rail based on multinomial logit model (MNL). Maximum likelihood estimation is adopted to calibrate the parameters. Finally, take Suzhou as an example to apply the model and analyze the sensitivity of each factor. The results shows that the URT share rate can be improved by reducing waiting time, access time, rail fares and increasing the speed of rail, among which reducing rail fares works best, reducing access time a little less and reducing waiting time the least.


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    Titel :

    Forecasting URT Share Rate Based on MNL Model


    Beteiligte:
    Tang, Liang (Autor:in) / Guo, Xiucheng (Autor:in) / Ran, Jiangyu (Autor:in) / He, Ming (Autor:in)

    Kongress:

    11th International Conference of Chinese Transportation Professionals (ICCTP) ; 2011 ; Nanjing, China


    Erschienen in:

    ICCTP 2011 ; 677-688


    Erscheinungsdatum :

    2011-07-26




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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