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Post-earthquake resilience assessment and long-term restoration prioritization of transportation network

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  • Wu, Yangyang
  • Hou, Guangyang
  • Chen, Suren

Abstract

An efficient and safe transportation system is essential to communities during the long-term recovery period after earthquakes. A disrupted transportation network due to infrastructure damage or failure affects the functionality of the traffic system and poses increased traffic safety risks. A rational assessment of the traffic network performance in terms of both traffic efficiency and safety cannot only provide comprehensive quantification of system resilience, but also enable more risk-informed post-hazard recovery planning. A new methodology to assess the resilience performance of transportation networks during post-earthquake long-term recovery period is developed in this study with two main innovative contributions: (1) modeling the traffic performance of partially closed road segments in the network simulation and optimization, which offers useful tool to capture the time-progressive recovery process; and (2) integrating both traffic efficiency and safety into the resilience assessment and recovery prioritization. After a resilience indicator is introduced to characterize the overall traffic efficiency and safety of the transportation network using probabilistic sampling method, a new restoration priority measure is proposed to support post-earthquake restoration of damaged bridges. A demonstrative study is conducted on a hypothetical network system located in an earthquake-prone area.

Suggested Citation

  • Wu, Yangyang & Hou, Guangyang & Chen, Suren, 2021. "Post-earthquake resilience assessment and long-term restoration prioritization of transportation network," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    • Handle: RePEc:eee:reensy:v:211:y:2021:i:c:s0951832021001575
    DOI: 10.1016/j.ress.2021.107612
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    15. Liu, Qiang & Tang, Aiping & Huang, Delong & Huang, Ziyuan & Zhang, Bin & Xu, Xiuchen, 2022. "Total probabilistic measure for the potential risk of regional roads exposed to landslides," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
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    18. Wang, Feng & Tian, Jin & Shi, Chenli & Ling, Jiamu & Chen, Zian & Xu, Zhengguo, 2024. "A multi-stage quantitative resilience analysis and optimization framework considering dynamic decisions for urban infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    19. Liu, Qiang & Huang, Delong & Zhang, Bin & Tang, Aiping & Xu, Xiuchen, 2024. "Developing a probability-based technique to improve the measurement of landslide vulnerability on regional roads," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    20. Geng, Sunyue & Liu, Sifeng & Fang, Zhigeng, 2022. "A demand-based framework for resilience assessment of multistate networks under disruptions," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    21. Yangyang Wu & Suren Chen, 2023. "Transportation Resilience Modeling and Bridge Reconstruction Planning Based on Time-Evolving Travel Demand during Post-Earthquake Recovery Period," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    22. Li, Yulong & Lin, Jie & Zhang, Chi & Zhu, Huaxing & Zeng, Saixing & Sun, Chengshaung, 2022. "Joint optimization of structure and protection of interdependent infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    23. Aghababaei, Mohammad T. (Siavash) & Costello, Seosamh B. & Ranjitkar, Prakash, 2021. "Measures to evaluate post-disaster trip resilience on road networks," Journal of Transport Geography, Elsevier, vol. 95(C).
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    25. Liu, Xiao & Xie, Qiang, 2024. "A probabilistic framework to evaluate seismic resilience of substations based on three-stage uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 249(C).

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