Abstract
Emergency evacuation of office buildings, in the event of a life-threatening situation such as a fire incident, is a function of various factors ranging from architectural to socio-behavioral ones. We show how individual-based modeling approaches such as molecular dynamics can be coupled with behavioral responses in panic situations, in order to quantify in a systematic way the impact of human familiarity to the space, during emergency evacuation. The ultimate goal is to identify certain crucial design features that can help in engineering better evacuation plans.
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References
Benthorn, L., & Frantzich, H. (1999). Managing evacuating people from facilities during a fire emergency. Facilities, 17, 325–330.
Blue, V. J., & Adler, J. L. (2000). Cellular automata microsimulation of bidirectional pedestrian flows. Journal of the Transportation Research Board, 1678, 135–141.
Burstedde, C., Klauck, K., Schadschneider, A., & Zittartz, J. (2001). Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A, 295, 507–525.
Cagdas, G., & Saglamer, G. (1995). A simulation model to predict the emptying times of buildings. Architectural Science Review, 38, 9–19.
Chertkoff, J., & Kushigian, R. (1999). Don’t panic: The psychology of emergency egress and ingress. London: Praeger.
Cova, T. J., & Johnson, J. P. (2002). Micro simulation of neighbourhood evacuations in the urban-wildland interface. Environment and Planning, A, 34, 2211–2229.
Daan, F., & Berend, S. (2002). Understanding molecular simulation: From algorithms to applications. San Diego: Academic.
Deere, S. J., Galea, E. R., & Lawrence, P. J. (2009). A systematic methodology to assess the impact of human factors in ship design. Applied Mathematical Modelling, 33, 867–883.
Dehne, M., & Kruse, D. (2007). Design of escape routes by simulating evacuation dynamics in conjunction with a probabilistic safety concept. Berlin: Springer.
Dijkstra, J., Jessurun, A. J., & Timmermans, H. J. P. (2001). A multi-agent cellular automata model of pedestrian movement. In M. Schreckenberg & S. D. Sharma (Eds.), Pedestrian and evacuation dynamics (pp. 173–181). Berlin: Springer.
Drager, K. H., Lovas, G. G., & Wiklund, J. (1992). EVACSIM—A comprehensive evacuation simulation tool. Proceedings of the 1992 International Emergency Management and Engineering Conference, Florida, 101–108.
Feinberg, W. E., & Johnson, N. R. (2000). Firescap: A computer simulation model of reaction to a fire alarm. Journal of Mathematical Sociology, 20(2–3), 247–269.
Frenkel, D., & Smit, B. (2002). Understanding molecular simulation: From algorithms to applications. San Diego: Academic.
Galea, E. R. (2001). Predicting evacuation and circulation in planes, trains, buildings and ships using the EXODUS software. Proceedings of Conference on Pedestrian and Evacuation Dynamics, Duisburg, Germany.
Galea, E. R., & Galparsoro, J. M. P. (1994). EXODUS: An evacuation model for mass transport vehicles. Fire Safety Journal, 22, 341–366.
Guo, D., Ren, B., & Wang, C. (2008). Integrated agent-based modeling with GIS for large scale emergency simulation. In Lecture Notes in Computer Science (pp. 618–625). Berlin: Springer.
Helbing, D. (1994). A mathematical model for the behavior of individuals in a social field. Journal of Mathematical Sociology, 19(3), 189–219.
Helbing, D. (1995). Theoretical foundation of macroscopic traffic models. Physica A, 219(3–4), 375–390.
Helbing, D. (2001). Traffic and related self-driven many-particle systems. Reviews of Modern Physics, 73, 1067–1141.
Helbing, D. (2003). Agent-based simulation of traffic jams, crowds, and supply networks: Reality, simulation, and design of intelligent infrastructures. Institute for Economics and Traffic, Dresden University of Technology, Germany.
Helbing, D., Farkas, I., & Vicsek, T. (2000). Simulating dynamical features of escape panic. Nature, 407, 487–490.
Helbing, D., & Molnar, P. (1995). Social force model for pedestrian dynamics. Physical Review, 51(5), 4282–4286.
Henderson, L. F. (1974). On the fluid mechanics of human crowd motion. Transportation Research, 8, 509–515.
International Standard (ISO) (2006). ISO 14520-1: Gaseous fire-extinguishing systems—Physical properties and system design, Part 1: General requirements. Switzerland: ISO.
Johnson, N. R. (1987). Panic and the breakdown of social order: Popular myth, social theory, empirical evidence. Sociological Focus, 20, 171–183.
Johnson, N. R., & Feinberg, W. E. (1997). The impact of exit instructions and number of exits in fire emergencies: A computer simulation investigation. Journal of Environmental Psychology, 17(2), 123–133.
Johnson, N. R., Stemler, J. G., & Hunter, D. (1977). Crowd behavior as “Risky Shift”: A laboratory experiment. Sociometry, 40, 183–187.
Ketchell, N., Cole, S. S., & Webber, D. M. (1993). The EGRESS code for human movement and behaviour in emergency evacuation. In R. A. Smith & J. F. Dickie (Eds.), Engineering for crowd safety (pp. 361–370). Amsterdam: Elsevier.
Kim, H., Park, J. H., & Lee, D. (2003). An experimental analysis on the mobility of evacuating passengers in ship with regard to listing and motion. Journal of Ship and Ocean Engineering, 35, 125–138.
Kim, H., Park, J. H., Lee, D., & Yang, Y. S. (2004). Establishing the methodologies for human evacuation simulation in marine accidents. Computers and Industrial Engineering, 46, 725–740.
Kisko, T. M., & Francis, R. L. (1985). EVACNET+: A computer program to determine optimal building evacuation plans. Fire Safety Journal, 9, 211–220.
Klüpfel, H., Meyer-König, M., Wahle, J., & Schreckenberg, M. (2000). Microscopic simulation of evacuation processes on passenger ships. In S. Bandini & T. Worsch (Eds.), 2000 (Theoretical and practical issues on cellular automata, pp. 63–71). Berlin: Springer.
Kwon, E., & Pitt, S. (2005). Evaluation of emergency evacuation strategies for downtown event traffic using a dynamic network model. Journal of the Transportation Research Board, 1922, 149–155.
Lämmel, G., Rieser, M., Nagel, K., Taubenboöck, Strunz, G., Gozeberg, N., et al. (2008). Emergency preparedness in the case of a tsounami-evacuation analysis and traffic optimization for the Indonesian city of Padang. In Pedestrian and Evacuation Dynamics Proceedings of the 4th Int. Conference, Wuppertal, Springer, Berlin.
Langley, A., Mintzberg, H., Pitcher, P., Posada, E., & Saint-Macary, J. (1995). Opening up decision making: The view from the black stool. Organization Science, 6, 260–279.
Lighthill, M. J., & Whitham, G. B. (1955). On kinematic waves: II a theory of traffic flow on long crowded roads. Proceedings of the Royal Society, London, Series A, 229, 317–345.
Lo, S. M., Fang, Z., Lin, P., & Zhi, G. S. (2004). An evacuation model: The SGEM package. Fire Safety Journal, 39(3), 169–190.
Mintz, A. (1951). No-adaptive group behavior. Journal Abnormal and Social Psychology, 46, 150–159.
Nagatani, T. (2002). The physics of traffic jams. Reports on progress in physics, 65, 1331–1386.
Nagel, K., & Schreckenberg, M. (1992). A cellular automaton model for freeway traffic. Journal de Physique I, 2, 2221–2229.
Nilsson, D., & Johansson, A. (2009). Social influence during the initial phase of a fire evacuation—Analysis of evacuation experiments in a cinema theatre. Fire Safety Journal, 44(1), 71–79.
Nishidate, K., & Baba, M. (1996). Cellular automaton model for random walkers. Physical Review Letters, 77(9), 1675–1678.
Oven, V. A., & Cakici, N. (2009). Modelling the evacuation of a high-rise office building in Istanbul. Fire Safety Journal, 44, 1–15.
Pan, X., Han, C. S., Dauber, K., & Law, K. H. (2007). A multi-agent based framework for the simulation of human and social behavior during emergency evacuations. AI and Society, 22(2), 113–132.
Parisi, D. R., & Dorso, C. O. (2005). Microscopic dynamics of pedestrian evacuation. Physica A, 354, 606–618.
Phillips, W. F. (1979). A kinetic model for traffic flow with continuum implications. Transportation Planning and Technology, 5, 131–138.
Prigogine, I., & Herman, R. (1971). Kinetic theory of vehicular traffic. New York: Elsevier.
Quarantelli, E. (1954). The nature and conditions of panic. The American Journal of Sociology, 60(3), 267–275.
Radwan, E. A., Hobeika, A. G., & Sivasailam, D. (1985). A computer simulation model for rural network evacuation under natural disasters. ITE Journal, 55, 25–30.
Raney, B., Cetin, N., Völlmy, A., Vrtic, M., Axhausen, K., & Nagel, K. (2003). An agent-based microsimulation model of Swiss travel: First results. Networks and Spatial Economics, 3, 23–41.
Rapaport, D. C. (2004). The art of molecular dynamics (2nd ed.). Cambridge: Cambridge University Press.
Richards, P. I. (1956). Shock waves on the highway. Operations Research, 4, 42–51.
Schadschneider, A., Klingsch, W., Klüpfel, H., Kretz, T., Rogsch, C., & Seyfried, A. (2008). Evacuation dynamics: Empirical results, modeling and applications. In R. A. Meyers (Ed.), Encyclopedia of complexity and system science. Berlin: Springer.
Shields, T. J., & Boyce, K. E. (2000). A study of evacuation from large retail stores. Fire Safety Journal, 35(1), 25–49.
Sime, J. D. (1985). Movement toward the familiar: Person and place affiliation in a fire entrapment setting. Environment and Behavior, 17(6), 697–724.
Sisiopiku, V. P. (2007). Application of traffic simulation modeling for improved emergency preparedness planning. Urban Planning and Development, 133, 51–60.
Thiago, T. P. (2005). An approach for modeling human cognitive behavior in evacuation models. Fire Safety Journal, 40(22), 177–189.
Thompson, P. A., & Marchant, E. W. (1995). A computer model for the evacuation of large building populations. Fire Safety Journal, 24, 131–148.
Vanem, E., & Skjong, R. (2005). Designing for safety in passenger ships utilizing advanced evacuation analyses—A risk based approach. Safety Science, 44, 111–135.
Vassalos D., Kim H., Christiansen G., Majumder J. (2001). A mesoscopic model for passenger evacuation in a virtual ship-sea environment and performance-based evaluation. Pedestrian and Evacuation Dynamics, April 4–6, 2001, Duisburg.
Watts, J. M. (2000). Rescuing truth from familiarity. Fire Technology, 36(1), 1–2.
Yamamoto, K., Kokubo, S., & Nishinari, K. (2007). Simulation for pedestrian dynamics by real-coded cellular automata (RCA). Physica A, 379, 654–660.
Acknowledgments
We wish to thank Dr. Nick Baker, Department of Architecture, University of Cambridge for his valuable suggestions. S. T. R. wishes to acknowledge support by the Cambridge, European Trust ESRC-MRC Interdisciplinary studentships and the A.G. Leventis Foundation. C. I. S. acknowledges partial support by the National Technical University of Athens through the Basic Research Program “Constantin Caratheodory.”
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Rassia, S.T., Siettos, C.I. Escape Dynamics in Office Buildings: Using Molecular Dynamics to Quantify the Impact of Certain Aspects of Human Behavior During Emergency Evacuation. Environ Model Assess 15, 411–418 (2010). https://doi.org/10.1007/s10666-009-9209-3
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DOI: https://doi.org/10.1007/s10666-009-9209-3