The deduction of passenger flow distribution is the basis of restoring normal operation order under train failure scenarios, and provides the basis for the formulation and implementation of train rescheduling and passenger flow control measures. In order to calculate passenger flow accurately and efficiently and ensure operation safety, a method for deducing the passenger flow spatial and temporal distribution is proposed to solve the above problems. Based on the route selection model, considering the changes of passengers’ travel behavior after failure, the function of passengers’ willingness to wait time is constructed to calculate the inbound passenger flow. Individual route choice behavior is updated according to the change of transport capacity, and reassign the route selection. The Multi-agent simulation modeling technology is used to dynamically deduce the temporal and spatial distribution of passenger flow. The empirical analysis of train faults in Hefei Metro shows that the average relative errors of the inbound and outbound stations of the fault line are 4.89% and 8.74%, respectively, which verifies the validity of the method to deduce the passenger flow distribution. In the fault scenario, compared with the normal operation scenario, the change rule of inbound traffic over time is similar but greatly reduced. The outbound passenger flow of a single station arrives at an interval, and the number of passengers in the interval is much greater than that in the same period and then slightly less than that in the same period.


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    Title :

    Spatial and Temporal Distribution of Passenger Flow on Urban Rail Transit Under Train Failure Scenarios


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Qin, Yong (editor) / Jia, Limin (editor) / Yang, Jianwei (editor) / Diao, Lijun (editor) / Yao, Dechen (editor) / An, Min (editor) / Deng, Xiaoke (author) / Chen, Yao (author) / Feng, Xujie (author) / Bai, Yun (author)

    Conference:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2023 ; Beijing, China October 19, 2023 - October 21, 2023



    Publication date :

    2024-02-03


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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