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Disruptions to Transportation Networks: A Review

In: Network Reliability in Practice

Author

Listed:
  • Shanjiang Zhu

    (University of Maryland)

  • David M. Levinson

    (University of Minnesota)

Abstract

Travel decisions may be very stable in a familiar environment. Major network disruptions such as the I-35W bridge collapse disrupt habitual behavior. Such “natural” experiments provide unique opportunities for behavioral studies, but the time window for such studies is limited. A well-developed methodology is crucial for both data collection and analysis, and thus the soundness of behavioral models, especially in such a limited time window. Therefore, this paper reviews both theoretical and empirical studies on traffic and behavioral impacts of network disruptions. Findings from this paper offer prospective ideas about capturing the impacts of network disruption.

Suggested Citation

  • Shanjiang Zhu & David M. Levinson, 2012. "Disruptions to Transportation Networks: A Review," Transportation Research, Economics and Policy, in: David M. Levinson & Henry X. Liu & Michael Bell (ed.), Network Reliability in Practice, edition 1, chapter 0, pages 5-20, Springer.
  • Handle: RePEc:spr:trachp:978-1-4614-0947-2_2
    DOI: 10.1007/978-1-4614-0947-2_2
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    Cited by:

    1. Shaun Larcom & Ferdinand Rauch & Tim Willems, 2017. "The Benefits of Forced Experimentation: Striking Evidence from the London Underground Network," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 2019-2055.
    2. Danczyk, Adam & Di, Xuan & Liu, Henry X. & Levinson, David M., 2017. "Unexpected versus expected network disruption: Effects on travel behavior," Transport Policy, Elsevier, vol. 57(C), pages 68-78.
    3. Liu, Luyu & Porr, Adam & Miller, Harvey J., 2024. "Measuring the impacts of disruptions on public transit accessibility and reliability," Journal of Transport Geography, Elsevier, vol. 114(C).
    4. Alireza Mostafizi & Haizhong Wang & Dan Cox & Lori A. Cramer & Shangjia Dong, 2017. "Agent-based tsunami evacuation modeling of unplanned network disruptions for evidence-driven resource allocation and retrofitting strategies," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1347-1372, September.
    5. Xuan Di & Henry X. Liu & Shanjiang Zhu & David Levinson, 2014. "Indifference Bands for Route Switching," Working Papers 000123, University of Minnesota: Nexus Research Group.
    6. Shanjiang Zhu & David Levinson & Henry Liu, 2017. "Measuring winners and losers from the new I-35W Mississippi River Bridge," Transportation, Springer, vol. 44(5), pages 905-918, September.
    7. Marcin Dziubinski & Sanjeev Goyal & Adrien Vigier, 2015. "Conflict and Networks," Cambridge Working Papers in Economics 1565, Faculty of Economics, University of Cambridge.
    8. Arkadiusz Adam Drabicki & Md Faqhrul Islam & Andrzej Szarata, 2021. "Investigating the Impact of Public Transport Service Disruptions upon Passenger Travel Behaviour—Results from Krakow City," Energies, MDPI, vol. 14(16), pages 1-14, August.
    9. Yeung, Timothy Yu-Cheong & Zhu, Dianzhuo, 2022. "Intercity ridesharing to the rescue: Capacity flexibility and price stability of BlaBlaCar during the 2018 French railway strike," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 270-290.
    10. Spyropoulou, Ioanna, 2020. "Impact of public transport strikes on the road network: The case of Athens," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 651-665.
    11. Caterina Malandri & Luca Mantecchini & Filippo Paganelli & Maria Nadia Postorino, 2021. "Public Transport Network Vulnerability and Delay Distribution among Travelers," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    12. Younes, Hannah & Nasri, Arefeh & Baiocchi, Giovanni & Zhang, Lei, 2019. "How transit service closures influence bikesharing demand; lessons learned from SafeTrack project in Washington, D.C. metropolitan area," Journal of Transport Geography, Elsevier, vol. 76(C), pages 83-92.
    13. Scagliarini, Tomas & Artime, Oriol & De Domenico, Manlio, 2025. "Assessing the vulnerability of empirical infrastructure networks to natural catastrophes," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).
    14. Xuan Di & Henry X. Liu & Shanjiang Zhu & David M. Levinson, 2017. "Indifference bands for boundedly rational route switching," Transportation, Springer, vol. 44(5), pages 1169-1194, September.
    15. Zoi Christoforou & Etienne Corbille & Nadir Farhi & Fabien Leurent, 2016. "Managing planned disruptions of mass transit systems," Post-Print hal-01240155, HAL.
    16. Malandri, Caterina & Mantecchini, Luca & Postorino, Maria Nadia, 2023. "A comprehensive approach to assess transportation system resilience towards disruptive events. Case study on airside airport systems," Transport Policy, Elsevier, vol. 139(C), pages 109-122.
    17. Mohammadi, Mehrdad & Jula, Payman & Tavakkoli-Moghaddam, Reza, 2019. "Reliable single-allocation hub location problem with disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 123(C), pages 90-120.
    18. Jafarian, Ahmad & Asgari, Nasrin & Mohri, Seyed Sina & Fatemi-Sadr, Elham & Farahani, Reza Zanjirani, 2019. "The inventory-routing problem subject to vehicle failure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 254-294.
    19. Lin, Teddy & Shalaby, Amer & Miller, Eric, 2016. "Transit User Behaviour in Response to Service Disruption: State of Knowledge," 57th Transportation Research Forum (51st CTRF) Joint Conference, Toronto, Ontario, May 1-4, 2016 319263, Transportation Research Forum.
    20. He, Sylvia Y. & Tao, Sui & Sun, Ka Kit, 2024. "Attitudes towards public transport under extended disruptions and massive-scale transit dysfunction: A Hong Kong case study," Transport Policy, Elsevier, vol. 149(C), pages 247-258.

    More about this item

    Keywords

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    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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