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

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  • Xuesong Feng
  • Mitsuru Saito
  • Quan Wang

Abstract

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.

Suggested Citation

  • Xuesong Feng & Mitsuru Saito & Quan Wang, 2017. "Reducing average comprehensive travel cost by rationally allocating trips to different travel modes," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(6), pages 679-688, August.
    • Handle: RePEc:taf:transp:v:40:y:2017:i:6:p:679-688
    DOI: 10.1080/03081060.2017.1325144
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    Cited by:

    1. Cai Jia & Yanyan Chen & Tingzhao Chen & Yanan Li & Luzhou Lin, 2022. "Evolutionary Game Analysis on Sharing Bicycles and Metro Strategies: Impact of Phasing out Subsidies for Bicycle–Metro Integration Model," Sustainability, MDPI, vol. 14(22), pages 1-20, November.

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