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Infrastructure-based transportation network vulnerability modeling and analysis

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  • Lu, Qing-Chang
  • Xu, Peng-Cheng
  • Zhang, Jingxiao

Abstract

Most studies evaluating impacts and consequences of disruptive events on transportation network performance have focused on the measurement of transportation network vulnerability from macroscopic perspectives. Few works explore the effects of road infrastructure attributes on network vulnerability from a mesoscopic perspective. Road sections with different infrastructure attributes could have different impacts on the vulnerability of transportation network under disruptions. Overlooking of these differences about attributes would produce inaccurate or incorrect results of vulnerability assessment as well as subsequent countermeasure suggestions. This study proposes an accessibility approach addressing attributes of road infrastructure to measure road network vulnerability. In particular, the methodology explores the impacts of road alignment and types on network degradation under accidents. This approach was tested on the highway network of Florida, USA. Results show that various road alignment and types could have different impacts on the accessibility of road network. Road network vulnerability is obviously affected by road alignment and types. When road sections are more curved, the network becomes more vulnerable under disruptions. More bridge and tunnel sections in transportation network would result in higher vulnerability of the highway network. This work could also assist decision makers when designing and managing road infrastructures under disasters.

Suggested Citation

  • Lu, Qing-Chang & Xu, Peng-Cheng & Zhang, Jingxiao, 2021. "Infrastructure-based transportation network vulnerability modeling and analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    • Handle: RePEc:eee:phsmap:v:584:y:2021:i:c:s0378437121006233
    DOI: 10.1016/j.physa.2021.126350
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    References listed on IDEAS

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