Under emergencies, reasonably guiding passenger flow can improve the transportation efficiency and minimize the impact of the accident on urban traffic operation. First of all, based on the psychological theory and the relevant information such as the choice preference of passengers, the passengers are classified to get the sensitivity difference of different potential mode passengers on the scheme attributes, which provides data support for path selection modeling and optimization. Secondly, the model with time index is established by using the data of the train and the passengers, and the model with comfort index is constructed by using the cubic polynomial fitting method. According to the utility maximization problem theory, the objective function including time and comfort index is constructed to provide the optimal path for different types of passengers. Finally, a case study of partial rail transit lines in Beijing is presented. The results show that, in the case of emergency, by analyzing the behavior preference of passenger's path selection, the passengers can be classified, and a more suitable route can be provided for each type of passengers, which can improve the time utilization ratio, and passengers' perception of the train's comfort.


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    Title :

    Applying choice preference to passenger flow guidance for urban rail transit under emergencies


    Contributors:
    Chen, Hao (editor) / Shangguan, Wei (editor) / Xu, Ran (author) / Xiao, Hongbing (author)

    Conference:

    Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024) ; 2024 ; Xi'an, China


    Published in:

    Proc. SPIE ; 13422


    Publication date :

    2025-01-20





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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