IDEAS home Printed from https://ideas.repec.org/p/cdl/itsrrp/qt1z913878.html
   My bibliography  Save this paper

Integrating Traffic Network Analysis and Communication Network Analysis at a Regional Scale to Support More Efficient Evacuation in Response to a Wildfire Event

Author

Listed:
  • Soga, Kenichi
  • Comfort, Louise
  • Zhao, Bingyu
  • Lorusso, Paola
  • Soysal, Sena

Abstract

As demonstrated by the Camp Fire evacuation, communications (city-to-city, city-to-residents) play important roles in coordinating traffic operations and safeguarding region-wide evacuation processes in wildfire events. This collaborative report across multiple domains (fire, communication and traffic), documents a series of simulations and findings of the wildfire evacuation process for resource-strapped towns in Northern California. It consists of: (1) meteorological and vegetation-status dependent fire spread simulation (cellular automata model); (2) agency-level and agency-to-residents communication simulation (system dynamics model); and (3) dynamic traffic assignment (spatial-queue model). Two case studies are conducted: one for the town of Paradise (and the surrounding areas) and another for the community of Bolinas. The data and models are based on site visits and interviews with local agencies and residents. The integrated simulation framework is used to assess the interdependencies among the natural environment, the evacuation traffic and the communication networks from an interdisciplinary point of view, to determine the performance requirements to ensure viable evacuation strategies under urgent, dynamic wildfire conditions. The case study simulations identify both potential traffic and communication bottlenecks. This research supports integrating fire, communication and traffic simulation into evacuation performance assessments.

Suggested Citation

  • 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.
  • Handle: RePEc:cdl:itsrrp:qt1z913878
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/1z913878.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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. 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.
    2. 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.
    3. 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.
    4. 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).
    5. Kun Yang & Rachel A. Davidson & Humberto Vergara & Randall L. Kolar & Kendra M. Dresback & Brian A. Colle & Brian Blanton & Tricia Wachtendorf & Jennifer Trivedi & Linda K. Nozick, 2019. "Incorporating inland flooding into hurricane evacuation decision support 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. 96(2), pages 857-878, March.
    6. Zhang, Nan & Huang, Hong & Su, Boni & Zhao, Jinlong, 2015. "Analysis of dynamic road risk for pedestrian evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 171-183.
    7. David Eichler & Hillel Bar-Gera & Meir Blachman, 2013. "Vortex-Based Zero-Conflict Design of Urban Road Networks," Networks and Spatial Economics, Springer, vol. 13(3), pages 229-254, September.
    8. Nagarajan, Magesh & Shaw, Duncan & Albores, Pavel, 2012. "Disseminating a warning message to evacuate: A simulation study of the behaviour of neighbours," European Journal of Operational Research, Elsevier, vol. 220(3), pages 810-819.
    9. Liu, Zhichen & Li, Ying & Zhang, Zhaoyi & Yu, Wenbo, 2022. "A new evacuation accessibility analysis approach based on spatial information," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    10. Jorge León & Alan March, 2016. "An urban form response to disaster vulnerability: Improving tsunami evacuation in Iquique, Chile," Environment and Planning B, , vol. 43(5), pages 826-847, September.
    11. 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.
    12. 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.
    13. Hector R. Lim & Ma. Bernadeth B. Lim & Mongkut Piantanakulchai, 2016. "Determinants of household flood evacuation mode choice in a developing country," 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. 84(1), pages 507-532, October.
    14. Xiangyang Cao & Bingzhong Zhou & Qiang Tang & Jiaqi Li & Donghui Shi, 2018. "Urban Wasteful Transport and Its Estimation Methods," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
    15. 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.
    16. Xiaozheng He & Srinivas Peeta, 2014. "Dynamic Resource Allocation Problem for Transportation Network Evacuation," Networks and Spatial Economics, Springer, vol. 14(3), pages 505-530, December.
    17. Urmila Pyakurel & Tanka Nath Dhamala & Stephan Dempe, 2017. "Efficient continuous contraflow algorithms for evacuation planning problems," Annals of Operations Research, Springer, vol. 254(1), pages 335-364, July.
    18. 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.
    19. 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.
    20. Li Liu & Huan Jin & Yangguang Liu & Xiaomin Zhang, 2022. "Intelligent Evacuation Route Planning Algorithm Based on Maximum Flow," IJERPH, MDPI, vol. 19(13), pages 1-14, June.

    More about this item

    Keywords

    Engineering; Social and Behavioral Sciences; Wildfires; evacuation; communications; simulation; traffic simulation; mathematical models; hazards and emergency operations; case studies;
    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:qt1z913878. 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.