To study the effect of different transport policies on reducing the average comprehensive travel cost (CTC) of all travel modes, by increasing public transport modal share and decreasing car trips, an optimization model is developed based on travel cost utility. A nested logit model is applied to analyze trip modal split. A Genetic Algorithm is then used to determine the implementation of optimal solutions in which various transport policies are applied in order to reduce average CTC. The central urban region of Beijing is selected as the study area in this research. Different policies are analyzed for comparison, focusing on their optimal impacts on minimizing the average CTC utility of all travel modes by rationally allocating trips to different travel modes in the study area. It is found that the proposed optimization model provides a reasonable indication of the effect of policies applied.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Reducing average comprehensive travel cost by rationally allocating trips to different travel modes




    Publication date :

    2017




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    55.80 / 74.75 / 55.80 Verkehrswesen, Transportwesen: Allgemeines / 74.75 Verkehrsplanung, Verkehrspolitik
    Local classification TIB:    770/7000



    Reducing average comprehensive travel cost by rationally allocating trips to different travel modes

    Feng, Xuesong / Saito, Mitsuru / Wang, Quan | Taylor & Francis Verlag | 2017




    Reducing Numbers of Vehicle Trips and Vehicle Miles of Travel Through Customized Travel Options

    Cleland, F. / Transportation Research Board | British Library Conference Proceedings | 2000


    Different Travel Patterns: Interzonal, Intrazonal, and External Trips

    Ahmed Hamdy Ghareib | British Library Online Contents | 1996