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Agent-Based Modeling and Analysis of Hurricane Evacuation Procedures for the Florida Keys

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  • Xuwei Chen
  • John Meaker
  • F. Zhan

Abstract

The unique geography of the Florida Keys presents both high risk of hurricane landfall and exceptional vulnerability to the effects of a hurricane strike. Inadequate hurricane shelters in the Keys make evacuation the only option for most residents, but the sole access road can become impassable well in advance of a major storm. These extraordinary conditions create challenges for emergency managers who must ensure that appropriate emergency plans are in place and to ensure that an orderly exodus can occur without stranding large numbers of people along an evacuation route with inadequate shelter capacity. This study attempts to answer two questions: (1) What is the minimum clearance time needed to evacuate all residents participating in an evacuation of the Florida Keys in advance of a major hurricane for 92,596 people – a population size calculated based on the 2000 US Census population data, census undercounts, and the number of tourists estimated to be in the area? (2) If a hurricane makes landfall in the Keys while the evacuation is in progress, how many residents will need to be accommodated if the evacuation route becomes impassable? The authors conducted agent-based microsimulations to answer the questions. Simulation results suggest that it takes 20 h and 11 min to 20 h and 14 min to evacuate the 92,596 people. This clearance time is less than the Florida state mandated 24-h clearance time limit. If one assumes that people evacuate in a 48-h period and the traffic flow from the Keys would follow that observed in the evacuation from Hurricane Georges, then a total of 460 people may be stranded if the evacuation route becomes impassable 48 h after an evacuation order is issued. If the evacuation route becomes impassable 40 h after an evacuation order is issued, then 14,000 people may be stranded. Copyright Springer 2006

Suggested Citation

  • Xuwei Chen & John Meaker & F. Zhan, 2006. "Agent-Based Modeling and Analysis of Hurricane Evacuation Procedures for the Florida Keys," 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. 38(3), pages 321-338, July.
  • Handle: RePEc:spr:nathaz:v:38:y:2006:i:3:p:321-338
    DOI: 10.1007/s11069-005-0263-0
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    Citations

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    Cited by:

    1. A. Kimms & K. Seekircher, 2016. "Network design to anticipate selfish evacuation routing," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 271-298, September.
    2. Kevin D. Henry & Nathan J. Wood & Tim G. Frazier, 2017. "Influence of road network and population demand assumptions in evacuation modeling for distant tsunamis," 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. 85(3), pages 1665-1687, February.
    3. Widener, Michael J. & Horner, Mark W., 2011. "A hierarchical approach to modeling hurricane disaster relief goods distribution," Journal of Transport Geography, Elsevier, vol. 19(4), pages 821-828.
    4. Laobing Zhang & Gabriele Landucci & Genserik Reniers & Nima Khakzad & Jianfeng Zhou, 2018. "DAMS: A Model to Assess Domino Effects by Using Agent‐Based Modeling and Simulation," Risk Analysis, John Wiley & Sons, vol. 38(8), pages 1585-1600, August.
    5. Minjun Kim & Gi-Hyoug Cho, 2020. "Influence of Evacuation Policy on Clearance Time under Large-Scale Chemical Accident: An Agent-Based Modeling," IJERPH, MDPI, vol. 17(24), pages 1-18, December.
    6. Margarethe Kusenbach & Jason Simms & Graham Tobin, 2010. "Disaster vulnerability and evacuation readiness: coastal mobile home residents in Florida," 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. 52(1), pages 79-95, January.
    7. Annetta Burger & Talha Oz & William G. Kennedy & Andrew T. Crooks, 2019. "Computational Social Science of Disasters: Opportunities and Challenges," Future Internet, MDPI, vol. 11(5), pages 1-31, April.
    8. Jian Li & Kaan Ozbay & Bekir Bartin, 2015. "Effects of Hurricanes Irene and Sandy in New Jersey: traffic patterns and highway disruptions during evacuations," 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. 78(3), pages 2081-2107, September.
    9. Shangde Gao & Yan Wang, 2021. "Assessing the impact of geo-targeted warning messages on residents’ evacuation decisions before a hurricane using agent-based modeling," 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. 107(1), pages 123-146, May.
    10. Lindell, Michael K., 2008. "EMBLEM2: An empirically based large scale evacuation time estimate model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 140-154, January.
    11. Qing Yang & Ying Sun & Xingxing Liu & Jinmei Wang, 2020. "MAS-Based Evacuation Simulation of an Urban Community during an Urban Rainstorm Disaster in China," Sustainability, MDPI, vol. 12(2), pages 1-19, January.
    12. Denissa Sari Darmawi Purba & Eleftheria Kontou & Chrysafis Vogiatzis, 2021. "Evacuation Route Planning for Alternative Fuel Vehicles," Papers 2109.01578, arXiv.org, revised May 2022.
    13. David Marasco & Pamela Murray-Tuite & Seth Guikema & Tom Logan, 2020. "Time to leave: an analysis of travel times during the approach and landfall of Hurricane Irma," 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. 103(2), pages 2459-2487, September.
    14. Cathal O'Donoghue & Karyn Morrissey & John Lennon, 2014. "Spatial Microsimulation Modelling: a Review of Applications and Methodological Choices," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 26-75.
    15. Akiko Masuya & Ashraf Dewan & Robert Corner, 2015. "Population evacuation: evaluating spatial distribution of flood shelters and vulnerable residential units in Dhaka with geographic information systems," 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. 78(3), pages 1859-1882, September.
    16. X Chen & F B Zhan, 2008. "Agent-based modelling and simulation of urban evacuation: relative effectiveness of simultaneous and staged evacuation strategies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(1), pages 25-33, January.
    17. Yu Han & Changjie Chen & Zhong-Ren Peng & Pallab Mozumder, 2022. "Evaluating impacts of coastal flooding on the transportation system using an activity-based travel demand model: a case study in Miami-Dade County, FL," Transportation, Springer, vol. 49(1), pages 163-184, February.
    18. Bertha Maya Sopha & Athaya Islami Triasari & Lynette Cheah, 2021. "Sustainable Humanitarian Operations: Multi-Method Simulation for Large-Scale Evacuation," Sustainability, MDPI, vol. 13(13), pages 1-19, July.
    19. Michael Widener & Mark Horner & Sara Metcalf, 2013. "Simulating the effects of social networks on a population’s hurricane evacuation participation," Journal of Geographical Systems, Springer, vol. 15(2), pages 193-209, April.

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