IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i10p4307-d1398106.html
   My bibliography  Save this article

Understanding Tsunami Evacuation via a Social Force Model While Considering Stress Levels Using Agent-Based Modelling

Author

Listed:
  • Constanza Flores

    (Transdisciplinary Science and Engineering Program, Graduate School of Advanced Science and Engineering, Hiroshima University, 1-5-1 Kagamiyama, Higashi-Hiroshima 739-8529, Japan
    Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch 8140, New Zealand
    School of Engineering, RMIT University, Melbourne, VIC 3000, Australia
    Second affiliation is current main affiliation.)

  • Han Soo Lee

    (Transdisciplinary Science and Engineering Program, Graduate School of Advanced Science and Engineering, Hiroshima University, 1-5-1 Kagamiyama, Higashi-Hiroshima 739-8529, Japan
    Center for the Planetary Health and Innovation Science (PHIS), The IDEC Institute, Hiroshima University, 1-5-1 Kagamiyama, Higashi-Hiroshima 739-8529, Japan)

  • Erick Mas

    (International Research Institute of Disaster Science, Tohoku University, Sendai 980-8572, Japan)

Abstract

Given massive events, such as demonstrations in coastal cities exposed to tsunamigenic earthquakes, it is essential to explore pedestrian motion methods to help at-risk coastal communities and stakeholders understand the current issues they face to enhance disaster preparedness. This research targets SDG 11 Sustainable Cities and Communities. It strengthens resilience in coastal areas by implementing a social force model using a microscopic agent-based model to assess the impact of human behaviour on evacuation performance by introducing evacuation stress levels due to a tsunami triggered in central Chile. Two scenarios with two environments and three crowd sizes are implemented in NetLogo. In Scenario 1, pedestrians walk at a relaxed velocity. In Scenario 2, tsunami evacuation stress is incorporated, resulting in pedestrians walking at a running velocity, taking, on average, four times less time to evacuate. We explored more realistic settings by considering the internal susceptibility of each agent to spread tsunami evacuation stress among other evacuees. Results from Scenario 2 show that internal susceptibility effects almost double the mean evacuation time for 200 agents. Findings suggest a trade-off between realism and the minimization of evacuation time. This research is considered a first step toward including stress in tsunami evacuations for sustainable evacuation planning.

Suggested Citation

  • Constanza Flores & Han Soo Lee & Erick Mas, 2024. "Understanding Tsunami Evacuation via a Social Force Model While Considering Stress Levels Using Agent-Based Modelling," Sustainability, MDPI, vol. 16(10), pages 1-20, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4307-:d:1398106
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/10/4307/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/10/4307/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xu Chen & Martin Treiber & Venkatesan Kanagaraj & Haiying Li, 2018. "Social force models for pedestrian traffic – state of the art," Transport Reviews, Taylor & Francis Journals, vol. 38(5), pages 625-653, September.
    2. Anders Johansson & Dirk Helbing & Pradyumn K. Shukla, 2007. "Specification Of The Social Force Pedestrian Model By Evolutionary Adjustment To Video Tracking Data," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(supp0), pages 271-288.
    3. Dirk Helbing & Lubos Buzna & Anders Johansson & Torsten Werner, 2005. "Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions," Transportation Science, INFORMS, vol. 39(1), pages 1-24, February.
    4. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    5. Nathan Wood & Mathew Schmidtlein, 2013. "Community variations in population exposure to near-field tsunami hazards as a function of pedestrian travel time to safety," 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. 65(3), pages 1603-1628, February.
    6. Ignacio A. Solís & Pedro Gazmuri, 2017. "Evaluation of the risk and the evacuation policy in the case of a tsunami in the city of Iquique, Chile," 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. 88(1), pages 503-532, August.
    7. Kretz, Tobias, 2015. "On oscillations in the Social Force Model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 272-285.
    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. Ma, Liang & Chen, Bin & Wang, Xiaodong & Zhu, Zhengqiu & Wang, Rongxiao & Qiu, Xiaogang, 2019. "The analysis on the desired speed in social force model using a data driven approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 894-911.
    2. Flötteröd, Gunnar & Lämmel, Gregor, 2015. "Bidirectional pedestrian fundamental diagram," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 194-212.
    3. Sticco, I.M. & Frank, G.A. & Dorso, C.O., 2021. "Social Force Model parameter testing and optimization using a high stress real-life situation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    4. Ziyou Gao & Yunchao Qu & Xingang Li & Jiancheng Long & Hai-Jun Huang, 2014. "Simulating the Dynamic Escape Process in Large Public Places," Operations Research, INFORMS, vol. 62(6), pages 1344-1357, December.
    5. Li, Xingli & Guo, Fang & Kuang, Hua & Zhou, Huaguo, 2017. "Effect of psychological tension on pedestrian counter flow via an extended cost potential field cellular automaton model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 487(C), pages 47-57.
    6. Hänseler, Flurin S. & Bierlaire, Michel & Farooq, Bilal & Mühlematter, Thomas, 2014. "A macroscopic loading model for time-varying pedestrian flows in public walking areas," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 60-80.
    7. Wang, Lei & Zhang, Qian & Cai, Yun & Zhang, Jianlin & Ma, Qingguo, 2013. "Simulation study of pedestrian flow in a station hall during the Spring Festival travel rush," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2470-2478.
    8. Tian, Jiangtao & Li, Xingli & Guo, Qinghua & Kuang, Hua, 2024. "Dynamics characteristic of pedestrians’ particular overtaking behavior based on an improved social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    9. Johansson, Fredrik & Peterson, Anders & Tapani, Andreas, 2015. "Waiting pedestrians in the social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 95-107.
    10. Zhao, Yongxiang & Li, Meifang & Lu, Xin & Tian, Lijun & Yu, Zhiyong & Huang, Kai & Wang, Yana & Li, Ting, 2017. "Optimal layout design of obstacles for panic evacuation using differential evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 175-194.
    11. Liu, Qiujia & Lu, Linjun & Zhang, Yijing & Hu, Miaoqing, 2022. "Modeling the dynamics of pedestrian evacuation in a complex environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    12. Shi, Xiaomeng & Xue, Shuqi & Feliciani, Claudio & Shiwakoti, Nirajan & Lin, Junkai & Li, Dawei & Ye, Zhirui, 2021. "Verifying the applicability of a pedestrian simulation model to reproduce the effect of exit design on egress flow under normal and emergency conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    13. Haghani, Milad, 2021. "The knowledge domain of crowd dynamics: Anatomy of the field, pioneering studies, temporal trends, influential entities and outside-domain impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    14. Kang, Zengxin & Zhang, Lei & Li, Kun, 2019. "An improved social force model for pedestrian dynamics in shipwrecks," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 355-362.
    15. Tian, Xiaoyong & Li, Kun & Kang, Zengxin & Peng, Yun & Cui, Hongjun, 2020. "Simulating the dynamical features of evacuation governed by periodic vibrations," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    16. Guo, Fang & Li, Xingli & Kuang, Hua & Bai, Yang & Zhou, Huaguo, 2016. "An extended cost potential field cellular automata model considering behavior variation of pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 630-640.
    17. Lasse Pedersen, 2009. "When Everyone Runs for the Exit," International Journal of Central Banking, International Journal of Central Banking, vol. 5(4), pages 177-199, December.
    18. Shiwakoti, Nirajan & Sarvi, Majid, 2013. "Understanding pedestrian crowd panic: a review on model organisms approach," Journal of Transport Geography, Elsevier, vol. 26(C), pages 12-17.
    19. Krbálek, Milan & Hrabák, Pavel & Bukáček, Marek, 2018. "Pedestrian headways — Reflection of territorial social forces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 38-49.
    20. Dirk Helbing & Pratik Mukerji, "undated". "Crowd Disasters as Systemic Failures: Analysis of the Love Parade Disaster," Working Papers ETH-RC-12-010, ETH Zurich, Chair of Systems Design.

    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:gam:jsusta:v:16:y:2024:i:10:p:4307-:d:1398106. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.