• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
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CAI Xuan, WANG Changlin. BeiDou Navigation Satellite System/Inertial Measurement Unit Integrated Train Positioning Method Based on Improved Unscented Kalman Filter Algorithm[J]. Journal of Southwest Jiaotong University, 2020, 55(2): 393-400. doi: 10.3969/j.issn.0258-2724.20170816
Citation: LIU Fengbo, ZHOU Tingliang, WANG Xiaomin. Calculation and Evaluation Method of Passenger Flow Distribution under Urban Rail Transit Failure[J]. Journal of Southwest Jiaotong University, 2021, 56(5): 921-927, 966. doi: 10.3969/j.issn.0258-2724.20200602

Calculation and Evaluation Method of Passenger Flow Distribution under Urban Rail Transit Failure

doi: 10.3969/j.issn.0258-2724.20200602
  • Received Date: 07 Sep 2020
  • Rev Recd Date: 16 Nov 2020
  • Available Online: 15 Apr 2021
  • Publish Date: 15 Oct 2021
  • In order to accurately obtain the impact of urban rail transit failures on passenger travel, the interaction states between passenger flow and train are modeled for passengers’ waiting, boarding and alighting processes. A calculation method is established for passenger flow distribution such as waiting passengers on platforms and passengers in carriages. The dynamic passenger flow simulation algorithm and evaluation indexes of passenger service level are designed. Taking an actual rail line under normal operation scenario as the reference, the space-time distribution of passenger flow under urban rail transit failure is computed and evaluated. The effect of waiting time on passenger flow distribution on platforms and in carriages and the effect of waiting time on passenger travel time are analyzed. The case study shows that, passengers wait a little longer on the platform instead of leaving, which will reduce part of travel time under the specific failure. However, the situations of high load rate in carriage and large passenger volume on platform increases, compared with the normal scenario. With the maximum waiting time increasing from 9 min to 15 min, the number of departing passengers decreases by 77.0%, the total travel time with penalty decreases by more than 10.0%, and the passenger retention rate is the same, but the maximum numbers of stranded passengers and waiting passengers increase by 94.1% and 29.6%, respectively.

     

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