A Novel Vulnerability Index and Approach for Improving Road Network Vulnerability
Loading...
Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
Canadian Science Publishing
Open Access Color
OpenAIRE Downloads
OpenAIRE Views
Abstract
A transportation network’s recovery depends on its vulnerability to disaster impacts and functionality restoration. This study proposes two novel indexes for comprehensively measuring the vulnerability of road networks: link vulnerability measurement and node vulnerability measurement. Analyses were conducted on a hypothetical road network using dynamic assignment in the PTV VISSIM microsimulation environment, and the network vulnerabilities were calculated using the proposed methods. The results were compared with those found in the literature. Additionally, a method was proposed to reduce the vulnerability of the road network, and the proposed approach was compared with the current situation. The results showed 13.09% and 14.83% improvements in the average link vulnerability and node vulnerability values, respectively. In terms of achieving a more balanced distribution of vulnerability across the system, improvements of 5.68% and 41.35% were observed in the standard deviations of the link vulnerability and node vulnerability values, respectively. © 2025 Elsevier B.V., All rights reserved.
Description
ORCID
Keywords
Microsimulation, Natural Disaster, Resilience, Road Network Protection, Vulnerability, Computer System Recovery, Motor Transportation, Network Security, Roads And Streets, Microsimulation, Natural Disasters, Network Protection, Network Vulnerability, Resilience, Road Network, Road Network Protection, Vulnerability, Vulnerability Index, Vulnerability Measurement, Disasters, Disaster Management, Natural Disaster, Transportation System, Vulnerability
Fields of Science
Citation
WoS Q
Q3
Scopus Q
Q2

OpenCitations Citation Count
N/A
Source
Canadian Journal of Civil Engineering
Volume
52
Issue
9
Start Page
1796
End Page
1811
PlumX Metrics
Citations
Scopus : 2
Captures
Mendeley Readers : 4
Google Scholar™

