China Safety Science Journal ›› 2023, Vol. 33 ›› Issue (6): 144-151.doi: 10.16265/j.cnki.issn1003-3033.2023.06.1434

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Passenger flow distribution method under urban rail transit operation interruption

ZHOU Huijuan1,2(), WENG Dongyang1, LI Bei3, WU Wenxiang1, ZHANG Zhe2   

  1. 1 Beijing Key Laboratory of Intelligent Control Technology for Urban Road Traffic, North China University of Technology, Beijing 100144, China
    2 State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
    3 Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China
  • Received:2023-01-10 Revised:2023-04-09 Online:2023-08-07 Published:2023-12-28

Abstract:

To accurately grasp the passenger flow distribution status under the condition of urban rail transit line operation interruption and improve the level of rail transit emergency response and decision-making, firstly, comprehensively considering the impact of train congestion and transfer behavior on passenger travel path, an impedance function based on passenger travel path was constructed to calculate the mean and variance of travel impedance and set the judgment conditions for selecting an effective path. Secondly, fully considering the limited rationality of passengers' risk and decision-making behavior in uncertain environment, the strategy of passenger route selection under line interruption was studied and analyzed based on cumulative prospect theory, the endogenous reference point based on travel time was set, and the cumulative foreground value of passenger travel path was calculated. Finally, a Logit-type stochastic equilibrium model of network passenger flow distribution under urban rail transit interruption was established. The model was solved by method of successive algorithm (MSA) and the weighted distribution of traffic on each path was realized by Matlab programming. The feasibility and validity of the model were verified by taking the actual interruption event of Beijing Metro Line 5 as an example. The results show that the error rate between the passenger flow distribution results of this model and the actual data of the passenger flow of Beijing Metro section is within ± 10% at each section, which can effectively identify and master the passenger route selection behavior under interruption, and can accurately identify the congested section conditions.

Key words: urban rail transit, operation interruption, cumulative prospect theory, stochastic equilibrium