To improve the efficiency of urban transportation systems and reduce congestion, this article focuses on the problem of dynamic traffic flow assignment with uncertain multimodal transportation demand. The objective is to minimize travel costs for commuters. We constructed a multimodal dynamic traffic flow allocation model with road capacity and solved it by combining variational inequalities with the MSA algorithm. The example analysis shows that the traffic volume allocation of different travel modes conforms to the Logit probability selection function, and the increase in the road network information perception coefficient makes travel mode selection more deterministic. This provides a new perspective for urban transportation planning and management.


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    Titel :

    Research on Elastic Demand Assignment of Multi-modal Urban Traffic Flow


    Weitere Titelangaben:

    Lecture Notes in Civil Engineering


    Beteiligte:
    Meng, Lingyun (Herausgeber:in) / Qian, Yongsheng (Herausgeber:in) / Bai, Yun (Herausgeber:in) / Lv, Bin (Herausgeber:in) / Tang, Yuanjie (Herausgeber:in) / Chen, Yangyang (Autor:in) / Yang, Juhua (Autor:in) / Wang, Jianjun (Autor:in) / Song, Qing (Autor:in) / Qu, Shilin (Autor:in)

    Kongress:

    International Conference on Traffic and Transportation Studies ; 2024 ; Lanzhou, China August 23, 2024 - August 25, 2024



    Erscheinungsdatum :

    21.11.2024


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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