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Quantitative assessment of the impacts of disruptive precipitation on surface transportation

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  • Bucar, Raif C.B.
  • Hayeri, Yeganeh M.

Abstract

This article addresses the impacts of flood events on urban street networks. Macro-traffic simulation techniques were used on disrupted and undisrupted scenarios to assess the increase on the network’s mobility and accessibility. Local topographical aspects of the terrain were analyzed to identify portions of the network more prone to disruption. Flood maps were used to systematically remove links from the network, generating its disrupted state for different scenarios. The traffic assignment model generated routes using k-shortest path methods with link impedance penalty functions, selecting them based on user equilibrium assumption. Simulation results indicated the viability of the method to analyze the impacts of flood events of different severity and duration. The successful validation of this method indicated its viability as a tool for benefit cost analysis of urban improvement projects including resilience plans for high risk cities. The analysis was validated using the City of Hoboken, New Jersey’s transportation network and flood models. Results can be applied to cities with a high chance of flooding and should help authorities to effectively review their infrastructure strategic plans as well as their short and long-term urban mobility plans.

Suggested Citation

  • Bucar, Raif C.B. & Hayeri, Yeganeh M., 2020. "Quantitative assessment of the impacts of disruptive precipitation on surface transportation," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    • Handle: RePEc:eee:reensy:v:203:y:2020:i:c:s0951832020306062
    DOI: 10.1016/j.ress.2020.107105
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    Cited by:

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    3. Lu, Qing-Long & Sun, Wenzhe & Dai, Jiannan & Schmöcker, Jan-Dirk & Antoniou, Constantinos, 2024. "Traffic resilience quantification based on macroscopic fundamental diagrams and analysis using topological attributes," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
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    5. 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).
    6. 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).
    7. Gururaghav Raman & Gurupraanesh Raman & Jimmy Chih-Hsien Peng, 2022. "Resilience of urban public electric vehicle charging infrastructure to flooding," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    8. Yu, Yun-Chi & Gardoni, Paolo, 2022. "Predicting road blockage due to building damage following earthquakes," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    9. Bucar, Raif C.B. & Hayeri, Yeganeh M., 2022. "Quantitative flood risk evaluation to improve drivers’ route choice decisions during disruptive precipitation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    10. Fahad, Md Golam Rabbani & Nazari, Rouzbeh & Motamedi, M.H. & Karimi, Maryam, 2022. "A Decision-Making Framework Integrating Fluid and Solid Systems to Assess Resilience of Coastal Communities Experiencing Extreme Storm Events," Reliability Engineering and System Safety, Elsevier, vol. 221(C).

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