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Research Articles

Exploring multi-modal evacuation strategies for a landlocked population using large-scale agent-based simulations

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Pages 1741-1783 | Received 10 Sep 2021, Accepted 20 Apr 2022, Published online: 16 May 2022

References

  • Aguilar, L., et al., 2019. Mass evacuation simulation considering detailed models: behavioral profiles, environmental effects, and mixed-mode evacuation. Asia Pacific Management Review, 24 (2), 114–123.
  • Al-Zinati, M., and Zalila-Wenkstern, R., 2018. A resilient agent-based re-organizing traffic network for urban evacuations. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 10978 LNAI, 42–58.
  • Al-Zinati, M., and Zalila-Wenkstern, R., 2015. Matisse 2.0: a large-scale multi-agent simulation system for agent-based its. 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2, 328–335.
  • Alexander, D.R., and Pescaroli, G., 2019. What are cascading disasters? UCL Open: Environment Preprint.
  • Anh, N.T.N., et al., 2011. A hybrid macro-micro pedestrians evacuation model to speed up simulation in road networks. In: International Conference on Autonomous Agents and Multiagent Systems. Springer, 371–383.
  • Bangate, J., et al., 2017. A review on the influence of social attachment on human mobility during crises. Albi: ISCRAM.
  • Battegazzorre, E., et al., 2021. Idealcity: a hybrid approach to seismic evacuation modeling. Advances in Engineering Software, 153, 102956.
  • Behrisch, M., et al., 2011. SumolschFromOnlineine2020.102956.1016/j.adveng. In: Proceedings of SIMUL 2011, The Third International Conference on Advances in System Simulation. ThinkMind.
  • Bernardini, G., et al., 2017. Flooding risk in existing urban environment: From human behavioral patterns to a microscopic simulation model. Energy Procedia, 134, 131–140.
  • Bianchin, G., and Pasqualetti, F., 2020. Gramian-based optimization for the analysis and control of traffic networks. IEEE Transactions on Intelligent Transportation Systems, 21 (7), 3013–3024..
  • Bosina, E., and Weidmann, U., 2017. Estimating pedestrian speed using aggregated literature data. Physica A: Statistical Mechanics and Its Applications, 468, 1–29.
  • Bourgais, M., Taillandier, P., and Vercouter, L., 2020. Ben: an architecture for the behavior of social agents. Journal of Artificial Societies and Social Simulation, 23 (4), 12.
  • Buchmueller, S., and Weidmann, U., 2006. Parameters of pedestrians, pedestrian traffic and walking facilities. IVT Schriftenreihe, 132, 1–58.
  • Chapuis, K., et al., 2021. An agent-based co-modeling approach to simulate the evacuation of a population in the context of a realistic flooding event: A case study in hanoi (vietnam). In: M.H. Mohd, M.Y. Misro, S. Ahmad and D. Nguyen Ngoc, eds. Modelling, simulation and applications of complex systems, Singapore. Springer Singapore, 79–108.
  • Chapuis, K., et al., 2019., Gen*: an integrated tool for realistic agent population synthesis. In: Advances in Social Simulation: Proceedings of the 15th Social Simulation Conference: 23cial Simulation: P. Springer Nature, 189.
  • Chapuis, K., et al., 2018. Gen*: a generic toolkit to generate spatially explicit synthetic populations. International Journal of Geographical Information Science, 32 (6), 1194–1210. Available from:.
  • Chooramun, N., Lawrence, P., and Galea, E., 2019. Investigating the application of a hybrid space discretisation for urban scale evacuation simulation. Fire Technology, 55 (2), 391–413..
  • Dang-Huu, T., et al., 2020. An agent-based model for mixed traffic in Vietnam based on virtual local lanes. In: 2020 12th International Conference on Knowledge and Systems Engineering (KSE). IEEE, 147–152.
  • Daudé, É., et al., 2019. Escape: Exploring by simulation cities awareness on population evacuation. In: Proceedings of the International ISCRAM Conference. vol. 2019-May, 76–93.
  • Fenet, J., and Daudé, É., 2020. Is population’s prevention the great failure of territorial risk management: The case of the industrial risks. Rouen, France: CyberGeo.
  • Geroliminis, N., and Daganzo, C.F., 2008. Existence of urban-scale macroscopic fundamental diagrams: some experimental findings. Transportation Research Part B: Methodological, 42 (9), 759–770.
  • Grimm, V., et al., 2020. The odd protocol for describing agent-based and other simulation models: a second update to improve clarity, replication, and structural realism. Journal of Artificial Societies and Social Simulation, 23 (2), 7.
  • Haghpanah, F., Schafer, B., and Castro, S., 2021. Application of bug navigation algorithms for large-scale agent-based evacuation modeling to support decision making. Fire Safety Journal, 122, 103322.
  • Hee, L., and Dunn, S., 2017. Urban mobility: 10 cities leading the way in Asia Pacific. Urban Land Institute (ULI) & Centre for Liveable Cities (CLC), 8 (16), 1–56.
  • Hemmati, M., et al., 2021. Shaping urbanization to achieve communities resilient to floods. Environmental Research Letters, 16 (9), 094033.
  • Hesham, O., and Wainer, G., 2021. Advanced models for centroidal particle dynamics: short-range collision avoidance in dense crowds. Simulation, 97 (8), 529–543.
  • IPCC, 2021. Climate change 2021. Cambridge: Cambridge University Press. Available from: https://www.ipcc.ch/report/ar6/wg1/.
  • Jin, S., et al., 2015. Estimating cycleway capacity and bicycle equivalent unit for electric bicycles. Transportation Research Part A: Policy and Practice, 77, 225–248.
  • Kesting, A., Treiber, M., and Helbing, D., 2007. General lane-changing model mobil for car-following models. Transportation Research Record: Journal of the Transportation Research Board, 1999 (1), 86–94.
  • Kim, J., Lee, S., and Lee, S., 2017. An evacuation route choice model based on multi-agent simulation in order to prepare Tsunami disasters. Transportmetrica B: Transport Dynamics, 5 (4), 385–401. Available from:.
  • Kim, M., and Cho, G.H., 2020. Influence of evacuation policy on clearance time under large-scale chemical accident: an agent-based modeling. International Journal of Environmental Research and Public Health, 17 (24), 9418–9442.
  • Knabb, R.D., Brown, D.P., and Rhome, J.R., 2006. Tropical cyclone report, Hurricane Rita. National Hurricane Center, 17, 18–26
  • Labbé, D., et al., 2019. Perception of park access and park use amongst youth in Hanoi: how cultural and local context matters. Landscape and Urban Planning, 189, 156–165.
  • Le, V.M., Vinh, H.T., and Zucker, J.D., 2017. Reinforcement learning approach for adapting complex agent-based model of evacuation to fast linear model. In: 2017 Seventh International Conference on Information Science and Technology (ICIST). 369–375.
  • Len, J., et al., 2020. Tsunami evacuation analysis in the urban built environment: a multi-scale perspective through two modeling approaches in via del mar, Chile. Coastal Engineering Journal, 62 (3), 389–404.
  • Li, Y., et al., 2019. Flood evacuation simulations using cellular automata and multiagent systems – a human-environment relationship perspective. International Journal of Geographical Information Science, 33 (11), 2241–2258.
  • Makinoshima, F., Imamura, F., and Abe, Y., 2018. Enhancing a tsunami evacuation simulation for a multi-scenario analysis using parallel computing. Simulation Modelling Practice and Theory, 83, 36–50.
  • Manson, S., et al., 2020. Methodological issues of spatial agent-based models. Journal of Artificial Societies and Social Simulation, 23 (1), 3.
  • Minh, C.C., Sano, K., and Matsumoto, S., 2005. The speed, flow and headway analyses of motorcycle traffic. Journal of the Eastern Asia Society for Transportation Studies, 6, 1496–1508.
  • Nagel, K., and Schreckenberg, M., 1992. A cellular automaton model for freeway traffic. Journal de Physique I, 2 (12), 2221–2229.
  • Nakasaka, Y., Ishigaki, T., and Kawanaka, R., 2020. A study on safe evacuation from inundated underground mall by a multi-agent model. In: 22nd Congress of the International Association for Hydro-Environment Engineering and Research-Asia Pacific Division, IAHR-APD 2020:020reating Resilience to Water-Related Challenges”. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104775272&partnerID=40&md5=dd65a1ddc68ff292efd572713ef5e27c.
  • Ngo, D.H., Tran, C., et al., 2010. Multi-agent based simulation of traffic in Vietnam. In: International Conference on Principles and Practice of Multi-Agent Systems. Springer, 636–648.
  • Oh, W., Yu, D., and Muneepeerakul, R., 2021. Efficiency-fairness trade-offs in evacuation management of urban floods: the effects of the shelter capacity and zone prioritization. PLoS One, 16 (6), e0253395.
  • Pan, Z., Wei, Q., and Wang, H., 2021. Agent-based simulation of hindering effect of small group behavior on elevated interval evacuation time along urban rail transit. Travel Behaviour and Society, 22, 262–273.
  • Parikh, N., Marathe, M., and Swarup, S., 2017. Integrating behavior and microsimulation models. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10051 LNAI, 39–59.
  • Parkin, J., and Rotheram, J., 2010. Design speeds and acceleration characteristics of bicycle traffic for use in planning, design and appraisal. Transport Policy, 17 (5), 335–341.
  • Pijls, W., and Post, H., 2009. Yet another bidirectional algorithm for shortest paths. Available from: https://ideas.repec.org/cgi-bin/htsearch?q=Yet+another+bidirectional+algorithm+for+shortest+paths.
  • Prédhumeau, M., Dugdale, J., and Spalanzani, A., 2021. Adapting the social force model for low density crowds in open environments. In: Springer Proceedings in Complexity, 519–531. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106404822&doi=10.1007%2f978-3-030-61503-1_49&partnerID=40&md5=3c557d68e1e29f317849a5f18d9837f5.
  • Reynolds, C.W., et al., 1999. Steering behaviors for autonomous characters. Game Developers Conference. Citeseer, 1999, 763–782.
  • Smith, L., Beckman, R., and Baggerly, K., 1995. Transims: transportation analysis and simulation system. Santa Fe, NM: Los Alamos National Lab.
  • Sun, H., et al., 2021. Self-organized crowd dynamics: research on earthquake emergency response patterns of drill-trained individuals based on GIS and multi-agent systems methodology. Sensors, 21 (4), 1–23.
  • Taillandier, F., et al., 2021. An agent-based model to simulate inhabitants behavior during a flood event. International Journal of Disaster Risk Reduction, 64, 102503.
  • Taillandier, P., 2014. Traffic simulation with the GAMA platform. In: International Workshop on Agents in Traffic and Transportation, France, 8. p. Available from: https://hal.archives-ouvertes.fr/hal-01055567.
  • Taillandier, P., et al., 2019. Building, composing and experimenting complex spatial models with the Gama platform. GeoInformatica, 23 (2), 299–322.
  • Thornton, C., et al., 2011., Pathfinder: an agent-based egress simulator. In: Pedestrian and evacuation dynamics. Cham: Springer, 889–892.
  • Tong, H., et al., 2011. Development of driving cycles for motorcycles and light-duty vehicles in Vietnam. Atmospheric Environment, 45 (29), 5191–5199.
  • Tranouez, P., Daudé, E., and Langlois, P., 2010. A multiagent urban traffic simulation. Journal of Nonlinear Systems and Applications, 1 (3), 9.
  • Treiber, M., Hennecke, A., and Helbing, D., 2000. Congested traffic states in empirical observations and microscopic simulations. Physical Review. E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 62 (2 Pt A), 1805–1824.
  • Valette, M., et al., 2018. Modeling a real-case situation of egress using BDI agents with emotions and social skills. In: International Conference on Principles and Practice of Multi-Agent Systems. Springer, 3–18.
  • Van den Berg, J., Lin, M., and Manocha, D., 2008. Reciprocal velocity obstacles for real-time multi-agent navigation. In: 2008 IEEE International Conference on Robotics and Automation. IEEE, 1928–1935.
  • Veeraswamy, A., et al., 2018. The simulation of urban-scale evacuation scenarios with application to the swinley forest fire. Safety Science, 102, 178–193.
  • Vorst, H.C., 2010. Evacuation models and disaster psychology. Procedia Engineering, 3, 15–21.
  • Wang, Z., et al., 2020. Analysis of flood evacuation process in vulnerable community with mutual aid mechanism: an agent-based simulation framework. International Journal of Environmental Research and Public Health, 17 (2), 560.
  • West, J., and Sherry, L., 2020. Agent-based simulation of metropolitan area evacuation by unmanned air mobility. In: Integrated Communications, Navigation and Surveillance Conference, ICNS. Vol. 2020-September. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094907511&doi=10.1109%2fICNS50378.2020.9222890&partnerID=40&md5=dc2b1cd75feac0adfb3ff8a9e41a8a1a.
  • Wijerathne, L., et al., 2018. Scalable HPC enhanced agent based system for simulating mixed mode evacuation of large urban areas. Transportation Research Procedia, 34, 275–282.
  • Yamazaki, T., et al., 2017. Urban disaster simulation incorporating human psychological models in evacuation behaviors. IFIP Advances in Information and Communication Technology, 501, 20–30.
  • Yang, L., et al., 2018. Assessment of flood losses with household responses: agent-based simulation in an urban catchment area. Environmental Modeling & Assessment, 23 (4), 369–388.
  • Yin, L., et al., 2020. Improving emergency evacuation planning with mobile phone location data. Environment and Planning B: Urban Analytics and City Science, 47 (6), 964–980.
  • Zebala, J., Ciepka, P., and RezA, A., 2012. Pedestrian acceleration and speeds. Problems of Forensic Sciences, 91, 227–234.

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