Journal of System Simulation
Abstract
Abstract: It is the basis of improving the safety guarantee ability of urban rail transit system to study and master the change law of the number of passengers in the urban rail transit station under the condition of Congestion Propagation. From the point of view of multi subsystem of passenger, station and train, combined with the multi-attribute characteristics of passenger flow, platform and train, the calculation model of the number of passengers in urban rail transit station is established based on system dynamics. A multi group sensitivity simulation experiment is designed to analyze the influence factors of the number of passengers on the platform from multiple perspectives. The results show that there is a great difference between the congestion propagation condition and the normal condition in the change of the number of passengers in the station. The train departure interval, passenger arrival rate and destination ratio have a great influence on the change of the number of passengers in the station, and the influence of the train arrival interval is relatively limited. The research results can provide a scientific basis for the development of passenger flow organization strategies for stations with specific passenger flow characteristics.
Recommended Citation
Chen, Wei; Li, Zongping; Liu, Can; and Ju, Yanni
(2022)
"Research on the Number of Passengers on the Platform of Rail Transit Station Considering Congestion Propagation,"
Journal of System Simulation: Vol. 34:
Iss.
7, Article 19.
DOI: 10.16182/j.issn1004731x.joss.21-0198
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol34/iss7/19
First Page
1582
Revised Date
2021-04-09
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.21-0198
Last Page
1592
CLC
TP391.9
Recommended Citation
Wei Chen, Zongping Li, Can Liu, Yanni Ju. Research on the Number of Passengers on the Platform of Rail Transit Station Considering Congestion Propagation[J]. Journal of System Simulation, 2022, 34(7): 1582-1592.
DOI
10.16182/j.issn1004731x.joss.21-0198
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons