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Published on 13 September 2023
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Alimu,K. (2023). Virtual Dynamic Marshalling of Trains under Severe Epidemic Situation. Advances in Economics, Management and Political Sciences,23,51-58.
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Virtual Dynamic Marshalling of Trains under Severe Epidemic Situation

Kamilijiang Alimu *,1,
  • 1 Beijing Jiaotong University

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2754-1169/23/20230352

Abstract

In the context of the global epidemic, urban rail transit has the risk of spreading the virus. Taking Beijing Metro Line 1 as an example, this project establishes a dynamic model of train variable marshalling by studying passenger behavior and virus transmission, aiming to explore more intelligent marshalling mode, optimize transportation organization, and improve the flexibility of train marshalling and dispatching of urban rail transit, so as to improve its transportation efficiency and reduce the station personnel density, Then reduce the risk of disease infection of passengers in the process of taking urban rail transit under the background of the outbreak. The results show that: Dynamic marshalling technology can significantly improve the transport efficiency of urban rail transit trains and effectively control the risk of infection of passengers.

Keywords

urban rail transit, virtual dynamic marshalling, epidemic

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Cite this article

Alimu,K. (2023). Virtual Dynamic Marshalling of Trains under Severe Epidemic Situation. Advances in Economics, Management and Political Sciences,23,51-58.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Management Research and Economic Development

Conference website: https://2023.icmred.org/
ISBN:978-1-915371-89-8(Print) / 978-1-915371-90-4(Online)
Conference date: 28 April 2023
Editor:Javier Cifuentes-Faura, Canh Thien Dang
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.23
ISSN:2754-1169(Print) / 2754-1177(Online)

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