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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2020  >  20(3): 120-128
CAO Yuan, WEN Jia-kun, MA Lian-chuan. Dynamic marshalling and scheduling of trains in major epidemics[J]. Journal of Traffic and Transportation Engineering, 2020, 20(3): 120-128. doi: 10.19818/j.cnki.1671-1637.2020.03.011
Citation: CAO Yuan, WEN Jia-kun, MA Lian-chuan. Dynamic marshalling and scheduling of trains in major epidemics[J]. Journal of Traffic and Transportation Engineering, 2020, 20(3): 120-128. doi: 10.19818/j.cnki.1671-1637.2020.03.011
shu

Dynamic marshalling and scheduling of trains in major epidemics

doi: 10.19818/j.cnki.1671-1637.2020.03.011
  • 1.

    National Engineering Research Center of Rail Transportation Operation and Control System, Beijing Jiaotong University, Beijing 100044, China

  • 2.

    School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China

Funds:

National Key Research and Development program of China 2018YFB1201601

More Information
  • Author Bio:

    CAO Yuan(1982-), male, professor, PhD, ycao@bjitu.edu.cn

  • Corresponding author: WEN Jia-kun(1996-), male, graduate student, 18120268@bjtu.edu.cn
  • Received Date: 2020-03-10
  • Publish Date: 2020-06-25
    Abstract
  • In order to reduce the infection risk of passengers who travel by urban rail transit in the context of the global epidemics outbreak, the marshalling and scheduling of trains were taking as the research objects, and a dynamic marshalling and scheduling method of trains based on the virtual coupling under the major epidemic was proposed. In order to improve the flexibility of train marshalling and scheduling in urban rail transit, the virtual coupling was applied to the train marshalling in urban rail transit. The nonlinear programming model of train dynamic marshalling based on the passenger flow was established to optimize the scheduling of urban rail transit trains, so as to improve the transport efficiency of urban rail transit, reduce the station personnel density and consequently reduce the risk of disease infection. The improved Wells-Riley model was used for the infection analysis. The pedestrian movement model based on the social force was used to calculate the parameters in the improved Wells-Riley model, so as to analyze the infection risk of passengers who travel under the dynamic marshalling of virtual coupling. The infection probability under the virtual coupling system was simulated and compared with the result under the traditional method by using the MATLAB. Analysis result shows that the virtual coupling technology can significantly improve the train transport efficiency of urban rail transit and shorten the tracking time interval between trains to 34.6 s. The dynamic marshalling and scheduling method of trains based on the virtual coupling can effectively reduce the infection risk of passengers. In the same conditions, the infection risk of passengers from the proposed method is only 85.1% of that from the traditional way, and the infection risks in the carriages and channel are 50.0% and 8.7% of those from the traditional way, respectively. If the proposed method is combined with the measures such as the control of off-peak travel and passenger flow, the in-station epidemic prevention and testing, the infection risk of passengers can reduce further.

     

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