Abstract
Large-scale population evacuation from urban areas may occur during disasters such as earth quakes, volcano eruptions, militarized conflicts, environmental disasters and more. Efficient and safe population evacuation is of great importance as it can save lives and reduce human suffering. The current study demonstrates an Agent-Based Simulation tool which may be used to support operational planning for population evacuation from threatened urban areas. The simulation models households as agents, each acting in accordance to a designated decision function, which renders the probability of evacuation as a function of the socioeconomic and demographic characteristics of the agents and the behavior of neighboring ones. Upon evacuation decision, agents embark on their way to their preassigned destinations, while their optimal route is calculated and updated periodically, based on road information (taken from Open-Street Map), accumulative traffic congestion, and simulated road conditions. The simulation calculates and records the location of all agents and enables the user to identify and analyze different evacuation scenarios, compare evacuation sequences, map and identify road bottlenecks, etc. Integrating such a simulation into the planning process—both at the municipal and the national levels—can significantly enhance authorities’ processes of preparing evacuation plans, including investing resources for developing safe evacuation destinations and educating the population for the unfolding of future emergencies. The main contribution of the current work is the ability to efficiently calculate optimal routes for millions of agents. To demonstrate this we applied the simulation on Kyiv (Ukraine), where a large number of its 3 million citizens have fled the city during Russia’s invasion on February 2022.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Kyiv region was obtained map from: https://geodata.lib.utexas.edu/catalog/stanford-pp624tm0074.
References
Chadefaux, T.: Early warning signals for war in the news. J. Peace Res. 51(1), 5–18 (2014)
Chen, C., Koll, C., Wang, H., Lindell, M.: An interdisciplinary agent-based evacuation model: integrating natural environment, built environment, and social system for community preparedness and resilience. Nat. Hazards Earth Syst. Sci. Disc. 2021, 1–27 (2021)
Collins, J., Ersing, R.L., Polen, A., Saunders, M.: Evacuation behavior measured during an evacuation order: an assessment of the effects of social connections on the decision to evacuate. Nat. Hazards Center (2018)
Dash, N., Gladwin, H.: Evacuation decision making and behavioral responses: individual and household. Nat. Hazards Rev. 8(3), 69–77 (2007)
Fredman, M.L., Tarjan, R.E.: Fibonacci heaps and their uses in improved network optimization algorithms. J. ACM (JACM) 34(3), 596–615 (1987)
Hagberg, A., Swart, P., S Chult, D.: Exploring network structure, dynamics, and function using networkx. Tech. rep., Los Alamos National Lab.(LANL), Los Alamos, NM (United States) (2008)
Hasan, S., Ukkusuri, S., Gladwin, H., Murray-Tuite, P.: Behavioral model to understand household-level hurricane evacuation decision making. J. Transp. Eng. 137(5), 341–348 (2011)
Hong, L., Frias-Martinez, V.: Modeling and predicting evacuation flows during hurricane IRMA. EPJ Data Sci. 9(1), 29 (2020)
Houts, P.S., Cleary, P.D.: Three Mile Island crisis: psychological, social, and economic impacts on the surrounding population. Penn State Press (2010)
Iklé, F.C., Kincaid, H.V.: Social Aspects of Wartime Evacuation of American Cities: With Particular Emphasis on Long-Term Housing and Reemployment, vol. 4, National Academy of Sciences, National Research Council (1956)
Kasereka, S., Kasoro, N., Kyamakya, K., Doungmo Goufo, E.F., Chokki, A.P., Yengo, M.V.: Agent-based modelling and simulation for evacuation of people from a building in case of fire. Procedia Comput. Sci. 130, 10–17 (2018). https://doi.org/10.1016/j.procs.2018.04.006, https://www.sciencedirect.com/science/article/pii/S1877050918303569, The 9th International Conference on Ambient Systems, Networks and Technologies (ANT 2018) / The 8th International Conference on Sustainable Energy Information Technology (SEIT-2018) / Affiliated Workshops
Kuligowski, E.: Predicting human behavior during fires. Fire Technol. 49(1), 101–120 (2013)
Newman, S.M.: The occasion instant: the structure of social responses to unanticipated air raid warnings (1963)
Norris, F.H.: Disaster research methods: past progress and future directions. J. Traumatic Stress: Off. Publ. Int. Soc. Traumatic Stress Stud. 19(2), 173–184 (2006)
OpenStreetMap contributors: Planet dump retrieved from https://planet.osm.org, https://www.openstreetmap.org (2017)
Paton, D., Johnston, D.: Disaster resilience: an integrated approach. Charles C Thomas Publisher (2017)
Raphael, B.: Individual and Community Responses to Trauma and Disaster: The Structure of Human Chaos. Cambridge University Press (1995)
Ren, C., Yang, C., Jin, S.: Agent-based modeling and simulation on emergency evacuation. In: Zhou, J. (ed.) Complex Scieces, pp. 1451–1461. Springer, Berlin Heidelberg, Berlin, Heidelberg (2009)
Silver, R.C., Holman, E.A., McIntosh, D.N., Poulin, M., Gil-Rivas, V.: Nationwide longitudinal study of psychological responses to September 11. JAMA 288(10), 1235–1244 (2002)
Tierney, K.: Disaster beliefs and institutional interests: recycling disaster myths in the aftermath of 9–11. In: Terrorism and Disaster: New Threats, New Ideas. Emerald Group Publishing Limited (2003)
Zhan, F.B., Chen, X.: Agent-based modeling and evacuation planning. In: Geospatial Technologies and Homeland Security, pp. 189–208. Springer (2008)
Zhang, W., Terrier, V., Fei, X., Markov, A., Duncan, S., Balchanos, M., Sung, W., Mavris, D., Loper, M., Whitaker, E., Riley, M.: Agent-Based Modeling of a Stadium Evacuation in a Smart City. pp. 2803–2814 (12 2018). https://doi.org/10.1109/WSC.2018.8632176
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Harari, E., Abudarham, N., Rokita, T. (2023). Evacuation Simulation for Large-Scale Urban Population. In: Squazzoni, F. (eds) Advances in Social Simulation. ESSA 2022. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-031-34920-1_10
Download citation
DOI: https://doi.org/10.1007/978-3-031-34920-1_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-34919-5
Online ISBN: 978-3-031-34920-1
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)