13
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Vulnerability assessment of freeway network considering the probabilities and consequences from a perspective based on network cascade failure

      research-article
      1 , 2 , * , , 2 , 1 , 1
      PLoS ONE
      Public Library of Science

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Freeway networks are vulnerable to natural disasters and man-made disruptions. The closure of one or more toll stations of the network often causes a sharp decrease in freeway performance. Therefore, measuring the probability and consequences of vulnerability to identify critical parts in the network is crucial for road emergency management. Most existing techniques only measure the consequences of node closure and rarely consider the probability of node closure owing to the lack of an extensive historical database; moreover, they ignore highways outside the study area, which can lead to errors in topological analysis and traffic distribution. Furthermore, the negative effects produced by the operation of freeway tunnels in vulnerability assessment have been neglected. In this study, a framework for freeway vulnerability assessment that considers both the probability and consequences of vulnerability is proposed, based on the perspective of network cascade failure analysis. The cascade failure analysis is conducted using an improved coupled map lattice model, developed by considering the negative effects of tunnels and optimizing the rules of local traffic redistribution. The perturbation threshold and propagation time step of network cascade failure are captured to reflect the probabilities and consequences of vulnerability. A nodal vulnerability index is established based on risk assessment, and a hierarchical clustering method is used to identify the vulnerability classification of critical nodes. The freeway network of Fuzhou in China is utilized to demonstrate the effectiveness of the proposed approach. Specifically, the toll stations in the study area are classified into five clusters of vulnerability: extremely high, high, medium, low, and extremely low. Approximately 31% of the toll stations were classified as the high or extremely high cluster, and three extremely vulnerable freeway sections requiring different precautions were identified. The proposed network vulnerability analysis method provides a new perspective to examine the vulnerability of freeway networks.

          Related collections

          Most cited references61

          • Record: found
          • Abstract: found
          • Article: not found

          Statistical mechanics of complex networks

          Reviews of Modern Physics, 74(1), 47-97
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            A Set of Measures of Centrality Based on Betweenness

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Vulnerability and resilience of transport systems – A discussion of recent research

                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: SoftwareRole: Writing – original draft
                Role: ConceptualizationRole: InvestigationRole: Methodology
                Role: Investigation
                Role: Project administrationRole: Supervision
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                14 March 2022
                2022
                : 17
                : 3
                : e0265260
                Affiliations
                [1 ] College of Transportation Engineering, Chang’an University, Xi’an, Shaanxi, China
                [2 ] College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
                University at Buffalo, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-0163-0883
                Article
                PONE-D-21-32528
                10.1371/journal.pone.0265260
                8920282
                35286346
                4c56221f-e8d1-4f33-b9f5-386163344c30
                © 2022 Xu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 10 October 2021
                : 24 February 2022
                Page count
                Figures: 15, Tables: 5, Pages: 28
                Funding
                Funded by: Special Fund for Science and Technology Innovation Project of Fujian Agricultural and Forestry University
                Award ID: KFA17035A
                Award Recipient :
                This research is supported by the “Special Fund for Science and Technology Innovation Project of Fujian Agricultural and Forestry University” (Grant No. KFA17035A). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Engineering and Technology
                Civil Engineering
                Transportation Infrastructure
                Roads
                Highways
                Engineering and Technology
                Transportation
                Transportation Infrastructure
                Roads
                Highways
                Engineering and Technology
                Civil Engineering
                Transportation Infrastructure
                Roads
                Engineering and Technology
                Transportation
                Transportation Infrastructure
                Roads
                Computer and Information Sciences
                Network Analysis
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Cluster Analysis
                Hierarchical Clustering
                Medicine and Health Sciences
                Public and Occupational Health
                Safety
                Traffic Safety
                Engineering and Technology
                Transportation
                Earth Sciences
                Natural Disasters
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Traumatic Injury Risk Factors
                Road Traffic Collisions
                Medicine and Health Sciences
                Public and Occupational Health
                Traumatic Injury Risk Factors
                Road Traffic Collisions
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article