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Identification of the critical accident causative factors in the urban rail transit system by complex network theory.

Authors :
Wang, Wenhao
Wang, Yanhui
Wang, Guangxing
Li, Man
Jia, Limin
Source :
Physica A. Jan2023, Vol. 610, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

Considering the complexity of the urban rail transit system (URTS), it is necessary to systematically identify the critical factors and their relationships to avoid or prevent urban rail transit accidents. In response to the problems few previous studies have modeled networks for the whole system components of URTS and have focused too much on the identification of specific component states or behaviors without quantitative analysis of inter-component relationships. This paper proposed a risk network construction and analysis method based on complex network theory to identify the critical accident causative factors and their relationships of the URTS system. Firstly, the accident is defined as the combination of a sequence of risk incidents occurring in a certain order and their resulting consequences, and the definitions of risk point and risk incident were given. Secondly, a risk network construction and analysis method based on the combination of accident reports and complex network theory was proposed to obtain the critical factors and their relationships in the process of the accident. At last, this paper constructed the urban rail transit risk point set containing 39 risk points, built the risk network based on 201 accident reports of URTS in China and analyzed the critical risk points and risk relationships. The results show that this study can provide a new perspective for identifying the critical causative factors of URTS accidents and their relationships for practical application in risk analysis and accident prevention. • The new definitions of risk points and incidents are put forward. • A critical risk analysis framework are proposed by complex network theory. • Critical risk points and relationships are identified in the urban rail transit system by the risk network. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03784371
Volume :
610
Database :
Academic Search Index
Journal :
Physica A
Publication Type :
Academic Journal
Accession number :
161303806
Full Text :
https://doi.org/10.1016/j.physa.2022.128404