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A user exposure based approach for non-structural road network vulnerability analysis

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Listed:
  • Lei Jin
  • Haizhong Wang
  • Binglei Xie
  • Le Yu
  • Lin Liu

Abstract

Aiming at the dense urban road network vulnerability without structural negative consequences, this paper proposes a novel non-structural road network vulnerability analysis framework. Three aspects of the framework are mainly described: (i) the rationality of non-structural road network vulnerability, (ii) the metrics for negative consequences accounting for variant road conditions, and (iii) the introduction of a new vulnerability index based on user exposure. Based on the proposed methodology, a case study in the Sioux Falls network which was usually threatened by regular heavy snow during wintertime is detailedly discussed. The vulnerability ranking of links of Sioux Falls network with respect to heavy snow scenario is identified. As a result of non-structural consequences accompanied by conceivable degeneration of network, there are significant increases in generalized travel time costs which are measurements for “emotionally hurt” of topological road network.

Suggested Citation

  • Lei Jin & Haizhong Wang & Binglei Xie & Le Yu & Lin Liu, 2017. "A user exposure based approach for non-structural road network vulnerability analysis," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-13, November.
    • Handle: RePEc:plo:pone00:0188790
    DOI: 10.1371/journal.pone.0188790
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    1. Lili Lu & Jian Wang & Pengjun Zheng & Wei Wang, 2017. "Network capacity with probit-based stochastic user equilibrium problem," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-19, February.
    2. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    3. Jenelius, Erik, 2009. "Network structure and travel patterns: explaining the geographical disparities of road network vulnerability," Journal of Transport Geography, Elsevier, vol. 17(3), pages 234-244.
    4. Chong Jin & Ruiying Li & Rui Kang, 2017. "Maximum flow-based resilience analysis: From component to system," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-26, May.
    5. Yuxin He & Jin Qin & Jian Hong, 2017. "Comparative analysis of quantitative efficiency evaluation methods for transportation networks," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-14, April.
    6. Yang, Hai & Bell, Michael G. H. & Meng, Qiang, 2000. "Modeling the capacity and level of service of urban transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(4), pages 255-275, May.
    7. Leng Jun-qiang & Yang Long-hai & Wei-yi Liu & Lin Zhao, 2017. "Measuring Road Network Vulnerability with Sensitivity Analysis," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-11, January.
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