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Assessing and Improving the Operational Resilience of a Large Highway Infrastructure System to Worst-Case Losses

Author

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  • David L. Alderson

    (Operations Research Department, Naval Postgraduate School, Monterey, California 93943)

  • Gerald G. Brown

    (Operations Research Department, Naval Postgraduate School, Monterey, California 93943)

  • W. Matthew Carlyle

    (Operations Research Department, Naval Postgraduate School, Monterey, California 93943)

  • R. Kevin Wood

    (Operations Research Department, Naval Postgraduate School, Monterey, California 93943)

Abstract

This paper studies the resilience of the regional highway transportation system of the San Francisco Bay Area. Focusing on peak periods for commuter traffic, traffic patterns are computed from a model that includes nonlinear increases in travel times due to congestion and reflects actual travel demands as captured by U.S. Census demographic data. We consider the consequences associated with loss of one or more road, bridge, and/or tunnel segments, where travelers are allowed to reroute to avoid congestion or potentially not travel at all if traffic is bad. We use a sequential game to identify sets of road, bridge, or tunnel segments whose loss results in worst-case travel times. We also demonstrate how the model can be used to quantify the operational resilience of the system, as well as to characterize trade-offs in resilience for different defensive investments, thus providing concise information to guide planners and decision makers.

Suggested Citation

  • David L. Alderson & Gerald G. Brown & W. Matthew Carlyle & R. Kevin Wood, 2018. "Assessing and Improving the Operational Resilience of a Large Highway Infrastructure System to Worst-Case Losses," Transportation Science, INFORMS, vol. 52(4), pages 1012-1034, August.
    • Handle: RePEc:inm:ortrsc:v:52:y:2018:i:4:p:1012-1034
    DOI: 10.1287/trsc.2017.0749
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    2. Jansuwan, Sarawut & Chen, Anthony & Xu, Xiangdong, 2021. "Analysis of freight transportation network redundancy: An application to Utah’s bi-modal network for transporting coal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 154-171.
    3. Xiao Feng & Shiwei He & Xuchao Chen & Guangye Li, 2021. "Mitigating the vulnerability of an air-high-speed railway transportation network: From the perspective of predisruption response," Journal of Risk and Reliability, , vol. 235(3), pages 474-490, June.
    4. Zhou, Yaoming & Kundu, Tanmoy & Qin, Wei & Goh, Mark & Sheu, Jiuh-Biing, 2021. "Vulnerability of the worldwide air transportation network to global catastrophes such as COVID-19," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    5. Gu, Yu & Chen, Anthony & Xu, Xiangdong, 2023. "Measurement and ranking of important link combinations in the analysis of transportation network vulnerability envelope buffers under multiple-link disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 118-144.

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