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Departure time choice behavior for hurricane evacuation planning: The case of the understudied medically fragile population

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  • Ng, ManWo
  • Diaz, Rafael
  • Behr, Joshua

Abstract

Despite the non-trivial number of (non-institutionalized) residents with special needs – referred to as the medically fragile population in this paper – there is virtually no research available to guide the hurricane evacuation planning for this population group. One area is their evacuation time choice behavior that can have tremendous implications for their safety as well as the logistics of the evacuation process. In this paper, we fundamentally advance our understanding of the evacuation timing behavior of this heavily understudied, and potentially vulnerable, population group. Analysis indicates that key differences exist between the medically fragile and non-medically fragile population.

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  • Ng, ManWo & Diaz, Rafael & Behr, Joshua, 2015. "Departure time choice behavior for hurricane evacuation planning: The case of the understudied medically fragile population," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 215-226.
    • Handle: RePEc:eee:transe:v:77:y:2015:i:c:p:215-226
    DOI: 10.1016/j.tre.2015.03.002
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    References listed on IDEAS

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    1. Ng, ManWo & Waller, S. Travis, 2010. "Reliable evacuation planning via demand inflation and supply deflation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 1086-1094, November.
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    4. Sheu, Jiuh-Biing, 2010. "Dynamic relief-demand management for emergency logistics operations under large-scale disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 1-17, January.
    5. Ng, ManWo & Behr, Joshua & Diaz, Rafael, 2014. "Unraveling the evacuation behavior of the medically fragile population: Findings from hurricane Irene," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 122-134.
    6. Goerigk, Marc & Deghdak, Kaouthar & Heßler, Philipp, 2014. "A comprehensive evacuation planning model and genetic solution algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 82-97.
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    Cited by:

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    3. David S. Dixon & Pallab Mozumder & William F. Vásquez & Hugh Gladwin, 2017. "Heterogeneity Within and Across Households in Hurricane Evacuation Response," Networks and Spatial Economics, Springer, vol. 17(2), pages 645-680, June.
    4. Wu, Lingxiao & Yang, Dong & Wang, Shuaian & Yuan, Yun, 2020. "Evacuating offshore working barges from a land reclamation site in storm emergencies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    5. Hemant Gehlot & Arif M. Sadri & Satish V. Ukkusuri, 2019. "Joint modeling of evacuation departure and travel times in hurricanes," Transportation, Springer, vol. 46(6), pages 2419-2440, December.
    6. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    7. Wong, Stephen D & Broader, Jacquelyn C & Shaheen, Susan A, 2020. "Can Sharing Economy Platforms Increase Social Equity for Vulnerable Populations in Disaster Response and Relief? A Case Study of the 2017 and 2018 California Wildfires," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1rm9b3r8, Institute of Transportation Studies, UC Berkeley.

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