Research on Chaotic Characteristics of Cascade Failure in Rail Transit Networks considering Nonlinear Load Fluctuations

The stable and efficient operation of rail transit networks (RTNs) is critical for the integrated development of metropolitan areas. However, numerous studies have indicated that RTNs are prone to large-scale cascading failures when subjected to disturbances. To address the limitations of traditiona...

Full description

Saved in:
Bibliographic Details
Main Authors: Changfeng Zhu, Zhaoxin Tang, Chun An, Jinhao Fang, Jie Wang, Linna Cheng
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2024/9093078
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832543674330775552
author Changfeng Zhu
Zhaoxin Tang
Chun An
Jinhao Fang
Jie Wang
Linna Cheng
author_facet Changfeng Zhu
Zhaoxin Tang
Chun An
Jinhao Fang
Jie Wang
Linna Cheng
author_sort Changfeng Zhu
collection DOAJ
description The stable and efficient operation of rail transit networks (RTNs) is critical for the integrated development of metropolitan areas. However, numerous studies have indicated that RTNs are prone to large-scale cascading failures when subjected to disturbances. To address the limitations of traditional cascading failure models, this paper proposes an innovative cascading failure model for metropolitan areas RTNs, which incorporates nonlinear load fluctuations and the bounded rationality of passengers. This model aims to capture the cascading failure characteristics of RTNs with chaotic properties under 12 combination strategies. A single- and dual-parameter coupling analysis of chaotic evolution parameters and prospect theory parameters are conducted. Taking the RTN in the Chengdu metropolitan area as an example, both the static characteristics and cascading failure features of the network are analyzed. The findings reveal the following: (i) the RTN is a assortativity network and lacks small-world and scale-free properties. (ii) During network disturbances, a higher level of passenger familiarity with the network increases the likelihood of large-scale cascading failures. (iii) When passengers tend to avoid risks, stations with higher carrying capacity are more prone to failures. This study holds significant implications for ensuring the stable and reliable operation of rail transit systems within metropolitan areas.
format Article
id doaj-art-de5c171cdd4f4a609d08b263449920db
institution Kabale University
issn 2042-3195
language English
publishDate 2024-01-01
publisher Wiley
record_format Article
series Journal of Advanced Transportation
spelling doaj-art-de5c171cdd4f4a609d08b263449920db2025-02-03T11:35:31ZengWileyJournal of Advanced Transportation2042-31952024-01-01202410.1155/2024/9093078Research on Chaotic Characteristics of Cascade Failure in Rail Transit Networks considering Nonlinear Load FluctuationsChangfeng Zhu0Zhaoxin Tang1Chun An2Jinhao Fang3Jie Wang4Linna Cheng5School of Traffic and TransportationSchool of Traffic and TransportationSchool of Traffic and TransportationSchool of Traffic and TransportationSchool of Traffic and TransportationSchool of Traffic and TransportationThe stable and efficient operation of rail transit networks (RTNs) is critical for the integrated development of metropolitan areas. However, numerous studies have indicated that RTNs are prone to large-scale cascading failures when subjected to disturbances. To address the limitations of traditional cascading failure models, this paper proposes an innovative cascading failure model for metropolitan areas RTNs, which incorporates nonlinear load fluctuations and the bounded rationality of passengers. This model aims to capture the cascading failure characteristics of RTNs with chaotic properties under 12 combination strategies. A single- and dual-parameter coupling analysis of chaotic evolution parameters and prospect theory parameters are conducted. Taking the RTN in the Chengdu metropolitan area as an example, both the static characteristics and cascading failure features of the network are analyzed. The findings reveal the following: (i) the RTN is a assortativity network and lacks small-world and scale-free properties. (ii) During network disturbances, a higher level of passenger familiarity with the network increases the likelihood of large-scale cascading failures. (iii) When passengers tend to avoid risks, stations with higher carrying capacity are more prone to failures. This study holds significant implications for ensuring the stable and reliable operation of rail transit systems within metropolitan areas.http://dx.doi.org/10.1155/2024/9093078
spellingShingle Changfeng Zhu
Zhaoxin Tang
Chun An
Jinhao Fang
Jie Wang
Linna Cheng
Research on Chaotic Characteristics of Cascade Failure in Rail Transit Networks considering Nonlinear Load Fluctuations
Journal of Advanced Transportation
title Research on Chaotic Characteristics of Cascade Failure in Rail Transit Networks considering Nonlinear Load Fluctuations
title_full Research on Chaotic Characteristics of Cascade Failure in Rail Transit Networks considering Nonlinear Load Fluctuations
title_fullStr Research on Chaotic Characteristics of Cascade Failure in Rail Transit Networks considering Nonlinear Load Fluctuations
title_full_unstemmed Research on Chaotic Characteristics of Cascade Failure in Rail Transit Networks considering Nonlinear Load Fluctuations
title_short Research on Chaotic Characteristics of Cascade Failure in Rail Transit Networks considering Nonlinear Load Fluctuations
title_sort research on chaotic characteristics of cascade failure in rail transit networks considering nonlinear load fluctuations
url http://dx.doi.org/10.1155/2024/9093078
work_keys_str_mv AT changfengzhu researchonchaoticcharacteristicsofcascadefailureinrailtransitnetworksconsideringnonlinearloadfluctuations
AT zhaoxintang researchonchaoticcharacteristicsofcascadefailureinrailtransitnetworksconsideringnonlinearloadfluctuations
AT chunan researchonchaoticcharacteristicsofcascadefailureinrailtransitnetworksconsideringnonlinearloadfluctuations
AT jinhaofang researchonchaoticcharacteristicsofcascadefailureinrailtransitnetworksconsideringnonlinearloadfluctuations
AT jiewang researchonchaoticcharacteristicsofcascadefailureinrailtransitnetworksconsideringnonlinearloadfluctuations
AT linnacheng researchonchaoticcharacteristicsofcascadefailureinrailtransitnetworksconsideringnonlinearloadfluctuations