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Clearance Time Estimation for Incorporating Evacuation Risk in Routing Strategies for Evacuation Operations

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  • Yu-Ting Hsu
  • Srinivas Peeta

Abstract

This study seeks to develop an approximate but efficient approach for estimating evacuation clearance time which is defined as the time required to evacuate the population of a location to areas of safety. Elsewhere, this estimate of the clearance time is used as input to infer evacuation risk for a location which reflects whether the population of that location can be safely evacuated before the disaster impacts it. As the computed evacuation risk is used in a real-time stage-based framework for evacuation operations, the approach for clearance time estimation needs to be computationally efficient while being capable of approximating traffic flow dynamics reasonably. To address these needs, a dynamic routing policy labeled the location-priority routing is proposed, and the associated clearance time estimation problem is formulated as a dynamic network flow problem. The location-priority is based on the lead time that a location has until it is impacted by the disaster, and designates that the population at a location with a shorter lead time has higher priority in using roadway capacity for evacuation. By combining the location-priority routing with the consideration of a super sink, the routing problem for the evacuation network is transformed into sequential single-origin single-destination dynamic routing problems. It avoids expensive iterative search processes, enabling computational efficiency for real-time evacuation operations. The solution approach approximately captures the evolution of traffic dynamics across the stages of the operational framework. Results from numerical experiments illustrate that the proposed approach can address the aforementioned needs related to clearance time estimation. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Yu-Ting Hsu & Srinivas Peeta, 2015. "Clearance Time Estimation for Incorporating Evacuation Risk in Routing Strategies for Evacuation Operations," Networks and Spatial Economics, Springer, vol. 15(3), pages 743-764, September.
    • Handle: RePEc:kap:netspa:v:15:y:2015:i:3:p:743-764
    DOI: 10.1007/s11067-013-9195-5
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    References listed on IDEAS

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    Cited by:

    1. Haluk Yapicioglu, 2018. "Multiperiod Multi Traveling Salesmen Problem Considering Time Window Constraints with an Application to a Real World Case," Networks and Spatial Economics, Springer, vol. 18(4), pages 773-801, December.
    2. Satish V. Ukkusuri & Samiul Hasan & Binh Luong & Kien Doan & Xianyuan Zhan & Pamela Murray-Tuite & Weihao Yin, 2017. "A-RESCUE: An Agent based Regional Evacuation Simulator Coupled with User Enriched Behavior," Networks and Spatial Economics, Springer, vol. 17(1), pages 197-223, March.

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