IDEAS home Printed from https://ideas.repec.org/p/cdl/itsrrp/qt78n6n8rf.html
   My bibliography  Save this paper

Testing Wildfire Evacuation Strategies and Coordination Plans for Wildland-Urban Interface (WUI) Communities in California

Author

Listed:
  • Soga, Kenichi PhD
  • Comfort, Louise PhD
  • Li, Pengshun
  • Zhao, Bingyu PhD
  • Lorusso, Paola

Abstract

In the event of a wildfire, government agencies need to make quick, well-informed decisions to safely evacuate people. Small communities, such as in Marin County, with a mix of residences and flammable vegetation in Wildland-Urban Interface zones tend to lack resources to conduct evacuation studies. Consequently, this study uses a framework of wildfire and traffic simulations to test the performance of potential evacuation strategies, including reducing the volume of evacuating vehicles through car-pooling, phasing evacuations by staggering evacuation times by zone, and prohibiting street parking in four representative areas of Marin County. Results show that reducing vehicle numbers lowers the average travel time by 20%-70% and average exposure time to wildfire by 27%-60% from the baseline. Phased evacuations with suitable time intervals lower the average travel time by 13.5%-70%, but may expose more vehicles to fire in some situations. Prohibiting street parking yields varying results due to different numbers of exits and evacuees. In some cases, prohibiting street parking reduces the average travel time by over 50%, while in other cases it only reduces the average travel time by 9%, contributing little to evacuation efficiency. Altogether, Marin County may want to consider developing a communication and parking plan to reduce the number of evacuating vehicles in wildfire situations. Phased evacuation is also highly recommended, but the suitable phasing interval depends on the speed of fire spread and number of evacuees. Further, whether to establish street parking prohibition policies for a certain area depends on the number of exits and the number of vehicles on the streets.

Suggested Citation

  • Soga, Kenichi PhD & Comfort, Louise PhD & Li, Pengshun & Zhao, Bingyu PhD & Lorusso, Paola, 2024. "Testing Wildfire Evacuation Strategies and Coordination Plans for Wildland-Urban Interface (WUI) Communities in California," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt78n6n8rf, Institute of Transportation Studies, UC Berkeley.
  • Handle: RePEc:cdl:itsrrp:qt78n6n8rf
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/78n6n8rf.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shahparvari, Shahrooz & Abbasi, Babak & Chhetri, Prem, 2017. "Possibilistic scheduling routing for short-notice bushfire emergency evacuation under uncertainties: An Australian case study," Omega, Elsevier, vol. 72(C), pages 96-117.
    2. Lim, Gino J. & Zangeneh, Shabnam & Reza Baharnemati, M. & Assavapokee, Tiravat, 2012. "A capacitated network flow optimization approach for short notice evacuation planning," European Journal of Operational Research, Elsevier, vol. 223(1), pages 234-245.
    3. Cova, Thomas J. & Johnson, Justin P., 2003. "A network flow model for lane-based evacuation routing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(7), pages 579-604, August.
    4. Zhao, Bingyu & Wong, Stephen D, 2021. "Developing Transportation Response Strategies for Wildfire Evacuations via an Empirically Supported Traffic Simulation of Berkeley, California," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt70p6k4rf, Institute of Transportation Studies, UC Berkeley.
    5. So, Stella K. & Daganzo, Carlos F., 2010. "Managing evacuation routes," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 514-520, May.
    6. Wong, Stephen & Shaheen, Susan PhD, 2019. "Current State of the Sharing Economy and Evacuations: Lessons from California," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt16s8d37x, Institute of Transportation Studies, UC Berkeley.
    7. Wong, Stephen D PhD & Broader, Jacquelyn C & Walker, Joan L PhD & Shaheen, Susan A PhD, 2022. "Understanding California wildfire evacuee behavior and joint choice making," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4fm7d34j, Institute of Transportation Studies, UC Berkeley.
    8. 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.
    9. Mozumder, Pallab & Raheem, Nejem & Talberth, John & Berrens, Robert P., 2008. "Investigating intended evacuation from wildfires in the wildland-urban interface: Application of a bivariate probit model," Forest Policy and Economics, Elsevier, vol. 10(6), pages 415-423, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Üster, Halit & Wang, Xinghua & Yates, Justin T., 2018. "Strategic Evacuation Network Design (SEND) under cost and time considerations," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 124-145.
    2. Esposito Amideo, A. & Scaparra, M.P. & Kotiadis, K., 2019. "Optimising shelter location and evacuation routing operations: The critical issues," European Journal of Operational Research, Elsevier, vol. 279(2), pages 279-295.
    3. Stephen D. Wong & Jacquelyn C. Broader & Joan L. Walker & Susan A. Shaheen, 2023. "Understanding California wildfire evacuee behavior and joint choice making," Transportation, Springer, vol. 50(4), pages 1165-1211, August.
    4. Pruttipong Apivatanagul & Rachel Davidson & Linda Nozick, 2012. "Bi-level optimization for risk-based regional hurricane evacuation planning," 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. 60(2), pages 567-588, January.
    5. E. Ronchi & J. Wahlqvist & A. Ardinge & A. Rohaert & S. M. V. Gwynne & G. Rein & H. Mitchell & N. Kalogeropoulos & M. Kinateder & N. Bénichou & E. Kuligowski & A. Kimball, 2023. "The verification of wildland–urban interface fire evacuation models," 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. 117(2), pages 1493-1519, June.
    6. Liu, Jialin & Jiang, Rui & Liu, Yang & Jia, Bin & Li, Xingang & Wang, Ting, 2024. "Managing evacuation of multiclass traffic flow: Fleet configuration, lane allocation, lane reversal, and cross elimination," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    7. Bretschneider, S. & Kimms, A., 2011. "A basic mathematical model for evacuation problems in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 523-539, July.
    8. Mukesh Rungta & Gino Lim & MohammadReza Baharnemati, 2012. "Optimal egress time calculation and path generation for large evacuation networks," Annals of Operations Research, Springer, vol. 201(1), pages 403-421, December.
    9. Grajdura, Sarah & Niemeier, Deb, 2022. "Improving Our Understanding of Fire Evacuation and Displacement Effects," Institute of Transportation Studies, Working Paper Series qt6h99c6j0, Institute of Transportation Studies, UC Davis.
    10. Gino J. Lim & M. Reza Baharnemati & Seon Jin Kim, 2016. "An optimization approach for real time evacuation reroute planning," Annals of Operations Research, Springer, vol. 238(1), pages 375-388, March.
    11. Özdamar, Linet & Ertem, Mustafa Alp, 2015. "Models, solutions and enabling technologies in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 244(1), pages 55-65.
    12. Shahparvari, Shahrooz & Abbasi, Babak, 2017. "Robust stochastic vehicle routing and scheduling for bushfire emergency evacuation: An Australian case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 32-49.
    13. Soga, Kenichi & Comfort, Louise & Zhao, Bingyu & Lorusso, Paola & Soysal, Sena, 2021. "Integrating Traffic Network Analysis and Communication Network Analysis at a Regional Scale to Support More Efficient Evacuation in Response to a Wildfire Event," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1z913878, Institute of Transportation Studies, UC Berkeley.
    14. Zhang, Zhao & Parr, Scott A. & Jiang, Hai & Wolshon, Brian, 2015. "Optimization model for regional evacuation transportation system using macroscopic productivity function," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 616-630.
    15. Vedat Bayram & Hande Yaman, 2018. "Shelter Location and Evacuation Route Assignment Under Uncertainty: A Benders Decomposition Approach," Transportation Science, INFORMS, vol. 52(2), pages 416-436, March.
    16. Xuedong Yan & Xiaobing Liu & Yulei Song, 2018. "Optimizing evacuation efficiency under emergency with consideration of social fairness based on a cell transmission model," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-21, November.
    17. Jiang-Hua Zhang & Hai-Yue Liu & Rui Zhu & Yang Liu, 2017. "Emergency Evacuation of Hazardous Chemical Accidents Based on Diffusion Simulation," Complexity, Hindawi, vol. 2017, pages 1-16, December.
    18. Gino Lim & M. Baharnemati & Seon Kim, 2016. "An optimization approach for real time evacuation reroute planning," Annals of Operations Research, Springer, vol. 238(1), pages 375-388, March.
    19. Jianghua Zhang & Yang Liu & Yingxue Zhao & Tianhu Deng, 2020. "Emergency evacuation problem for a multi-source and multi-destination transportation network: mathematical model and case study," Annals of Operations Research, Springer, vol. 291(1), pages 1153-1181, August.
    20. Rambha, Tarun & Nozick, Linda K. & Davidson, Rachel & Yi, Wenqi & Yang, Kun, 2021. "A stochastic optimization model for staged hospital evacuation during hurricanes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).

    More about this item

    Keywords

    Engineering; Wildfires; evacuation; urban areas; greenways; traffic simulation; advanced traveler information systems; street parking;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:itsrrp:qt78n6n8rf. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucbus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.