Chinese Science Bulletin

, 47:1484 | Cite as

Occupant evacuation model based on cellular automata in fire

  • Lizhong Yang
  • Weifeng Fang
  • Rui Huang
  • Zhihua Deng


By applying the rules set in traffic flow and pedestrian flow models, a basic cellular automata model is presented to simulate occupant evacuation in fire. Some extended models are introduced to study the special phenomena of evacuation from the fire room. The key of the models is the introduction of the danger grade which makes the route choice convenient and reasonable. Fire not only influences the emotional and behavioral characteristics of an individual but also affects his physical constitution, which reduces his maximal possible velocity. The models consider these influence factors by applying a set of simple but effective rules. It is needed to emphasize that all rules are established according to the essential phenomenon in fire evacuation, that is, all the occupants would try to move to the safest place as fast as possible. Some simulation examples are also presented to validate the applicability of the models.


cellular automata pedestrian flow fire occupant evacuation model 


  1. 1.
    Von, N. J., Burks, A. W., Theory of Self-reproducing Automata, Urbana: University of Illinois Press, 1966.Google Scholar
  2. 2.
    Wolfram, S., Theory and Applications of Cellular Automata, Singapore: World Scientific, 1986.Google Scholar
  3. 3.
    Wolfram, S., Cellular Automata and Complexity, Baltimore: Addison-Wesley Publishing Company, 1994.Google Scholar
  4. 4.
    Kai, N., Michael, S., A cellular automaton model for freeway traffic, J. Phys. I., 1992, 2(12): 2221.Google Scholar
  5. 5.
    Fukui, M., Ishibashi, Y., Traffic flow in 1D cellular automaton model including cars moving with high speed, J. Phys. Soc. Jpn., 1996, 65(6): 1868.CrossRefGoogle Scholar
  6. 6.
    Rickert, M., Nagel, K., Schreckenberg, M. et al., Two-lane traffic simulations using cellular automata, Physica A, 1996, 231(4): 534.CrossRefGoogle Scholar
  7. 7.
    Simon, P. M., Gutowitz, H. A., Cellular automaton model for bi-directional traffic, Physical Review E, 1998, 57(2): 2441.CrossRefGoogle Scholar
  8. 8.
    Wolfman, D., Cellular automata for traffic simulations, Physica A, 1999, 263(1–4): 438.Google Scholar
  9. 9.
    Sasvari, M., Kertesz, J., Cellular automata models of single lane traffic, Physical Review E, 1997, 56(4): 4104.CrossRefGoogle Scholar
  10. 10.
    Biham, O., Middleton, A. A., Levine, D., Self-organization and dynamical transition in traffic-flow models, Physical Review A, 1992, 46(10): 6124.CrossRefGoogle Scholar
  11. 11.
    Chowdhury, A. D., Schadschneider, A., Self-organization of traffic jams in cities: Effects of stochastic dynamics and signal periods, Physical Review E: Rapid Communications (AIP, USA), 1999, 59(2): 1311.Google Scholar
  12. 12.
    Special Report 209: Highway Capacity Manual. Transportation Research Board, Chapter 13, Washington, D.C.: National Research Council, 1985.Google Scholar
  13. 13.
    Blue, V. J., Adler, J. L., Emergent fundamental pedestrian flows from cellular automata microsimulation, Transportation Research Record, 1998, (1644): 29.Google Scholar
  14. 14.
    Blue, V. J., Adler, J. L., Bi-directional emergent fundamental pedestrian flows from cellular automata microsimulation, Proceedings of the 14th International Symposium on Transportation and Traffic Theory, (ed. Ceder, A.), Oxford: Pergamon Press, 1999, 235–254.Google Scholar
  15. 15.
    Blue, V. J., Adler, J. L., Cellular automata microsimulation for modeling bi-directional pedestrian walkways, Forthcoming in Transportation Research B-METH, 2001, 35(3): 293.CrossRefGoogle Scholar
  16. 16.
    Blue, V. J., Adler, J. L., Modeling four-directional pedestrian flows, Transportation Research Board, 2000, 1705: 43.CrossRefGoogle Scholar
  17. 17.
    Helbing, D., Molnar, P., Social force model for pedestrian dynamics, Physical Review E, 1995, 51(5): 4282.CrossRefGoogle Scholar
  18. 18.
    Virkler, M. R., Elayadath, S., Pedestrian speed-flow-density relationships, Transportation Research Record, 1994, 1438: 51.Google Scholar
  19. 19.
    Lovas, G. G., Modeling and simulation of pedestrian traffic flow, Transportation Research B, 1994, 28(6): 429.CrossRefGoogle Scholar
  20. 20.
    AlGadhi, S., Mahmassani, H., Simulation of crowd behavior and movement: Fundamental relations and application, Transportation Research Record, 1991, 1320: 260.Google Scholar
  21. 21.
    Helbing, D., Farkas, L., Vicsek, T., Simulating dynamical features of escape panic, Nature, 2000, 407(28): 486.Google Scholar
  22. 22.
    Burstedde, C., Klauck, K., Schadschneider, A. et al., Simulation of pedestrian dynamics using a two-dimensional cellular automaton, Physica A, 2001, 295(3–4): 507.CrossRefGoogle Scholar
  23. 23.
    Levin, B. C., Braun, E., Navarro, M. et al., Further development of the n-gas mathematics model—an approach for predicting the toxic potency of complex combustion mixtures, American Chemical Society, 1995, 599: 293.Google Scholar
  24. 24.
    Gwynne, S., Galea, E. R., Owen, M. et al., A review of the methodologies used in evacuation modeling, Fire and Materials, 1999, 23(6): 383.CrossRefGoogle Scholar
  25. 25.
    Ashe, B., Shields, T. J., Analysis and modelling of the unannounced evacuation of a large retail store, Fire and Materials, 1999, 23(6): 333.CrossRefGoogle Scholar
  26. 26.
    Hartzell, G. E., Engineering analysis of hazards to life safety in fires: The fire effluent toxicity component, Safety Science, 2001, 38(2): 147.CrossRefGoogle Scholar
  27. 27.
    Sekizawa, A., Ebihara, M., Notakeet, H. et al., Occupants’ behaviour in response to the high-rise apartments fire in Hiroshima city, Fire and Materials, 1999, 23(6): 297.CrossRefGoogle Scholar
  28. 28.
    Ozel, F., Time press and stress as a factor during emergency egress, Safety Science, 2001, 38(2): 95.CrossRefGoogle Scholar
  29. 29.
    Bak, P., How nature works: The science of self-organized criticality, Nature, 1996, 383(6603): 772.Google Scholar

Copyright information

© Science in China Press 2002

Authors and Affiliations

  • Lizhong Yang
    • 1
  • Weifeng Fang
    • 1
  • Rui Huang
    • 1
  • Zhihua Deng
    • 1
  1. 1.State Key Laboratory of Fire ScienceUniversity of Science and Technology of ChinaHefeiChina

Personalised recommendations