Influence Scope of Cascading Failure on Rail Transit System

被引：0

作者：

Xiong Z.-H. ^{[1
]}

Yao Z.-S. ^{[2
]}

机构：

[1] Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing

[2] Beijing Municipal Institute of City Planning and Design, Beijing

来源：

Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2020年 / 20卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Congestion propagation; Coupled map lattices (CML); Influence threshold; Passenger flow; Rail transit; Urban traffic;

D O I：

10.16097/j.cnki.1009-6744.2020.01.003

中图分类号：

学科分类号：

摘要：

Passenger aggregation, station congestion and congestion spread in the rail transit system infect by multiple factors and lead to cascading failure that means congestion spread to the whole network. To estimate the congestion propagation range of rail transit is an effective way to reduce the impact of uncertainty. The coupled map lattices (CML) model was proposed in this paper. Based on the principle of congestion propagation on rail transit system, the parameters such as physical structure, the initial transportation states and the volume of passenger flow, were combined into CML model and obtained by the historical passenger flow data. Three scenes were discussed under different parameters combinations. It can be shown that the initial states and coupling coefficient have significant influence on the range of congestion propagation. The range has no significant relation with the physical structure. The scale and range of congestion station can be obtained through CML model with the respondent network, initial states and coupling coefficients. It is benefic for improving the reliability of rail transit system. Copyright © 2020 by Science Press.

引用

页码：12 / 18

页数：6

共 7 条

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