Modelling cascade dynamics of passenger flow congestion in urban rail transit network induced by train delay

Li, M; Zhou, X; Wang, Y; Jia, L; An, M

Abstract

A research into congestion propagation mechanism of urban rail transit passenger flow in train delay scenario is of great significance to the formulation of coordinated limitation measures of passenger flow among the operation lines in urban rail transit networks. This paper presents a methodology for modelling cascade dynamics of passenger flow congestion. In this method, firstly, a computing method of network passenger flow states based on load entropy is proposed to describe the overall load conditions of passenger flow in the network. Secondly, a rail transit network is developed and the computation formulas of load and capacity of nodes have been established combining with a comprehensive consideration of nodes’ topological passenger flow attributes. Thirdly, Trip Betweenness Centrality of nodes is proposed and calculated. Considering the function of rail transit line capacity and load distribution strategy, the passenger flow congestion in train delay scenario is established to calculate cascade dynamics of congestion and the state transition of urban rail transit network. A real case study on Beijing Metro Line 10 is used to demonstrate the proposed methodology. The results show that the load values of nodes and the distances from the initial failure nodes can be determined for the spreading scope of passenger flow congestion in disrupted metro line and adjacent metro lines.

Citation

Li, M., Zhou, X., Wang, Y., Jia, L., & An, M. (2022). Modelling cascade dynamics of passenger flow congestion in urban rail transit network induced by train delay. Alexandria engineering journal : AEJ, 61(11), 8797-8807. https://doi.org/10.1016/j.aej.2022.02.022

• Journal Article Type: Article
• Acceptance Date: Feb 9, 2022
• Online Publication Date: Feb 19, 2022
• Publication Date: Nov 1, 2022
• Deposit Date: Mar 8, 2022
• Publicly Available Date: Mar 8, 2022
• Journal: Alexandria Engineering Journal
• Print ISSN: 1110-0168
• Publisher: Elsevier
• Volume: 61
• Issue: 11
• Pages: 8797-8807
• DOI: https://doi.org/10.1016/j.aej.2022.02.022
• Publisher URL: https://doi.org/10.1016/j.aej.2022.02.022
• Related Public URLs: https://www.journals.elsevier.com/alexandria-engineering-journal
• Additional Information: Access Information : This is an open access paper; Funders : State Key Laboratory of Rail Traffic Control and Safety;Youth Program of the National Natural Science Foundation; Projects : Railway Safety Assessment;Railway Infrastructure Development & Innovation; Grant Number: RCS2020ZT004; Grant Number: 52002019