Literature DB >> 18325875

Attacker-defender models and road network vulnerability.

M G H Bell1, U Kanturska, J-D Schmöcker, A Fonzone.   

Abstract

The reliability of road networks depends directly on their vulnerability to disruptive incidents, ranging in severity from minor disruptions to terrorist attacks. This paper presents a game theoretic approach to the analysis of road network vulnerability. The approach posits predefined disruption, attack or failure scenarios and then considers how to use the road network so as to minimize the maximum expected loss in the event of one of these scenarios coming to fruition. A mixed route strategy is adopted, meaning that the use of the road network is determined by the worst scenario probabilities. This is equivalent to risk-averse route choice. A solution algorithm suitable for use with standard traffic assignment software is presented, thereby enabling the use of electronic road navigation networks. A variant of this algorithm suitable for risk-averse assignment is developed. A numerical example relating to the central London road network is presented. The results highlight points of vulnerability in the road network. Applications of this form of network vulnerability analysis together with improved solution methods are discussed.

Year:  2008        PMID: 18325875     DOI: 10.1098/rsta.2008.0019

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  4 in total

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Journal:  PLoS One       Date:  2017-11-27       Impact factor: 3.240

2.  Measuring Road Network Vulnerability with Sensitivity Analysis.

Authors:  Leng Jun-Qiang; Yang Long-Hai; Wei-Yi Liu; Lin Zhao
Journal:  PLoS One       Date:  2017-01-26       Impact factor: 3.240

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

Authors:  Jinqiang Xu; Hainan Huang; Yanqiu Cheng; Kuanmin Chen
Journal:  PLoS One       Date:  2022-03-14       Impact factor: 3.240

4.  Quantifying the resilience of rapid transit systems: A composite index using a demand-weighted complex network model.

Authors:  Hong En Tan; Jeremy Hong Wen Oon; Nasri Bin Othman; Erika Fille Legara; Christopher Monterola; Muhamad Azfar Ramli
Journal:  PLoS One       Date:  2022-04-28       Impact factor: 3.752

  4 in total

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