Cascade Invulnerability of an Urban Agglomeration Highway–Railway Composite Network Considering Node Differences

Urban agglomeration transport network is affected by risks such as internal failure, natural disasters or deliberate attacks, which can easily lead to functional fragmentation and make it difficult to meet the needs of regional economic and social security development. Thus, large-scale network paralysis caused by the failure of a few stations or lines in the urban transport network has become an important practical problem that needs to be solved urgently. Therefore, based on the complex network theory, this paper constructs the traffic subnetwork and composite network of urban agglomeration considering node differences, establishes the cascade failure model, and analyses the cascade invulnerability of urban agglomeration traffic network under the incomplete information attack strategy with the help of numerical computing software simulation. The highway-railway composite network of the Shandong Peninsula urban agglomeration is taken as an example for empirical analysis. Research results can be analyzed in the critical nodes of the network, which can further provide theoretical references for the optimization of the transport system. This will improve the security and stability of the transport network and help to improve the security level of the national comprehensive transport network.

Authors

Institutions

Publication Details

Journal
Journal of Infrastructure Systems
Published
2025-04-29
DOI
https://doi.org/10.1061/jitse4.iseng-2568
Primary Topic
Evacuation and Crowd Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cascade Invulnerability of an Urban Agglomeration Highway–Railway Composite Network Considering Node Differences

Ya Li, Zhiguo Shao, Long Li, Li Mengdi et al.
Journal of Infrastructure Systems
Evacuation and Crowd Dynamics
article

Cascade Invulnerability of an Urban Agglomeration Highway–Railway Composite Network Considering Node Differences

Ya Li, Zhiguo Shao, Long Li, Li Mengdi, Tang Hongxia
article en

Abstract

Urban agglomeration transport network is affected by risks such as internal failure, natural disasters or deliberate attacks, which can easily lead to functional fragmentation and make it difficult to meet the needs of regional economic and social security development. Thus, large-scale network paralysis caused by the failure of a few stations or lines in the urban transport network has become an important practical problem that needs to be solved urgently. Therefore, based on the complex network theory, this paper constructs the traffic subnetwork and composite network of urban agglomeration considering node differences, establishes the cascade failure model, and analyses the cascade invulnerability of urban agglomeration traffic network under the incomplete information attack strategy with the help of numerical computing software simulation. The highway-railway composite network of the Shandong Peninsula urban agglomeration is taken as an example for empirical analysis. Research results can be analyzed in the critical nodes of the network, which can further provide theoretical references for the optimization of the transport system. This will improve the security and stability of the transport network and help to improve the security level of the national comprehensive transport network.

Journal of Infrastructure SystemsVol. 31(3)
Tongji University (CN), Qingdao University of Science and Technology (CN), Qingdao University of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 89%
Evacuation and Crowd Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.