IDEAS home Printed from https://ideas.repec.org/a/kap/netspa/v17y2017i1d10.1007_s11067-016-9323-0.html
   My bibliography  Save this article

A-RESCUE: An Agent based Regional Evacuation Simulator Coupled with User Enriched Behavior

Author

Listed:
  • Satish V. Ukkusuri

    (Purdue University)

  • Samiul Hasan

    (CSIRO, Cities Program, Land & Water Flagship)

  • Binh Luong

    (Purdue University)

  • Kien Doan

    (Urban-Civil Works Construction Investment Management Authority of Ho Chi Minh City)

  • Xianyuan Zhan

    (Purdue University)

  • Pamela Murray-Tuite

    (Department of Civil and Environmental Engineering, Virginia Tech)

  • Weihao Yin

    (Department of Civil and Environmental Engineering, Virginia Tech)

Abstract

Household behavior and dynamic traffic flows are the two most important aspects of hurricane evacuations. However, current evacuation models largely overlook the complexity of household behavior leading to oversimplified traffic assignments and, as a result, inaccurate evacuation clearance times in the network. In this paper, we present a high fidelity multi-agent simulation model called A-RESCUE (Agent-based Regional Evacuation Simulator Coupled with User Enriched behavior) that integrates the rich activity behavior of the evacuating households with the network level assignment to predict and evaluate evacuation clearance times. The simulator can generate evacuation demand on the fly, truly capturing the dynamic nature of a hurricane evacuation. The simulator consists of two major components: household decision-making module and traffic flow module. In the simulation, each household is an agent making various evacuation related decisions based on advanced behavioral models. From household decisions, a number of vehicles are generated and entered in the evacuation transportation network at different time intervals. An adaptive routing strategy that can achieve efficient network-wide traffic measurements is proposed. Computational results are presented based on simulations over the Miami-Dade network with detailed representation of the road network geometry. The simulation results demonstrate the evolution of traffic congestion as a function of the household decision-making, the variance of the congestion across different areas relative to the storm path and the most congested O-D pairs in the network. The simulation tool can be used as a planning tool to make decisions related to how traffic information should be communicated and in the design of traffic management policies such as contra-flow strategies during evacuations.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:netspa:v:17:y:2017:i:1:d:10.1007_s11067-016-9323-0
    DOI: 10.1007/s11067-016-9323-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11067-016-9323-0
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11067-016-9323-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tao Yao & Supreet Mandala & Byung Chung, 2009. "Evacuation Transportation Planning Under Uncertainty: A Robust Optimization Approach," Networks and Spatial Economics, Springer, vol. 9(2), pages 171-189, June.
    2. Gunnar Flötteröd & Yu Chen & Kai Nagel, 2012. "Behavioral Calibration and Analysis of a Large-Scale Travel Microsimulation," Networks and Spatial Economics, Springer, vol. 12(4), pages 481-502, December.
    3. Sherali, Hanif D. & Carter, Todd B. & Hobeika, Antoine G., 1991. "A location-allocation model and algorithm for evacuation planning under hurricane/flood conditions," Transportation Research Part B: Methodological, Elsevier, vol. 25(6), pages 439-452, December.
    4. 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.
    5. 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.
    6. 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.
    7. Michael Lindell & Jung Kang & Carla Prater, 2011. "The logistics of household hurricane evacuation," 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. 58(3), pages 1093-1109, September.
    8. Gipps, P. G., 1986. "A model for the structure of lane-changing decisions," Transportation Research Part B: Methodological, Elsevier, vol. 20(5), pages 403-414, October.
    9. 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.
    10. Robert Herman & Elliott W. Montroll & Renfrey B. Potts & Richard W. Rothery, 1959. "Traffic Dynamics: Analysis of Stability in Car Following," Operations Research, INFORMS, vol. 7(1), pages 86-106, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. Guy Wachtel & Jan-Dirk Schmöcker & Yuval Hadas & Yuhan Gao & Oren E Nahum & Boaz Ben-Moshe, 2021. "Planning for tourist urban evacuation routes: A framework for improving the data collection and evacuation processes," Environment and Planning B, , vol. 48(5), pages 1108-1125, June.
    4. 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.
    5. Chang, Kuo-Hao & Wu, Ying-Zheng & Su, Wen-Ray & Lin, Lee-Yaw, 2024. "A simulation evacuation framework for effective disaster preparedness strategies and response decision making," European Journal of Operational Research, Elsevier, vol. 313(2), pages 733-746.

    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. 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).
    2. 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.
    3. Xiaozheng He & Hong Zheng & Srinivas Peeta & Yongfu Li, 2018. "Network Design Model to Integrate Shelter Assignment with Contraflow Operations in Emergency Evacuation Planning," Networks and Spatial Economics, Springer, vol. 18(4), pages 1027-1050, December.
    4. 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.
    5. Souza, Juliano Silva & Lim-Apo, Flávio Araújo & Varella, Leonardo & Coelho, Antônio Sérgio & Souza, João Carlos, 2022. "Multi-period optimization model for planning people allocation in shelters and distributing aid with special constraints," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    6. Hiroshi Tatsumi & Masaya Kawano & Tetsunobu Yoshitake & Satoshi Toi & Yoshitaka Kajita, 2004. "Evaluation of City Planning Road Development Measures by Microscopic Traffic Simulation," ERSA conference papers ersa04p221, European Regional Science Association.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Kai Nagel & Peter Wagner & Richard Woesler, 2003. "Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling," Operations Research, INFORMS, vol. 51(5), pages 681-710, October.
    12. 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.
    13. Saadatseresht, Mohammad & Mansourian, Ali & Taleai, Mohammad, 2009. "Evacuation planning using multiobjective evolutionary optimization approach," European Journal of Operational Research, Elsevier, vol. 198(1), pages 305-314, October.
    14. Adam Pel & Michiel Bliemer & Serge Hoogendoorn, 2012. "A review on travel behaviour modelling in dynamic traffic simulation models for evacuations," Transportation, Springer, vol. 39(1), pages 97-123, January.
    15. 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.
    16. Yunyue He & Zhong Liu & Jianmai Shi & Yishan Wang & Jiaming Zhang & Jinyuan Liu, 2015. "K-Shortest-Path-Based Evacuation Routing with Police Resource Allocation in City Transportation Networks," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-23, July.
    17. Kimms, A. & Maiwald, M., 2018. "Bi-objective safe and resilient urban evacuation planning," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1122-1136.
    18. Li, Anna C.Y. & Nozick, Linda & Xu, Ningxiong & Davidson, Rachel, 2012. "Shelter location and transportation planning under hurricane conditions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 715-729.
    19. Hediye Tuydes-Yaman & Athanasios Ziliaskopoulos, 2014. "Modeling demand management strategies for evacuations," Annals of Operations Research, Springer, vol. 217(1), pages 491-512, June.
    20. 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.

    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:kap:netspa:v:17:y:2017:i:1:d:10.1007_s11067-016-9323-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.