Human Behavior Under Emergency and Its Simulation Modeling: A Review

  • Yixuan ChengEmail author
  • Dahai Liu
  • Jie Chen
  • Sirish Namilae
  • Jennifer Thropp
  • Younho Seong
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 780)


An emergency is a serious, unexpected, and potentially life-threatening situation requiring immediate action. Emergency evacuation is the most critical step to save people’s lives. The purpose of this paper is to provide a review of various factors to investigate human behavior under emergency situations. Computational modeling and simulation as a practical way to replicate human behavior change requires quantifying psychological and physical parameters. Previous studies on humans and animals, as well as common simulation approaches were reviewed. According to the results of this literature review, future experiments or simulations can consider not only physical parameters such as human dynamics, but also quantifying psychological parameters such as interpersonal relationship, goal-seeking behavior, decision-making differences, and many more.


Human factors Simulation modeling Evacuation Emergency 


  1. 1.
    Alexander, D.E.: Definition of emergency. In: Penuel, K.B., Statler, M., Hagen, R. (eds.) Encyclopedia of Crisis Management, pp. 324–325. SAGE Publications, Thousand Oaks (2013)Google Scholar
  2. 2.
    Fagel, M.J., Krill, S., Lawrence, M.: Policy and laws relating to emergency management planning. In: Fagel, M.J. (ed.) Crisis Management and Emergency Planning: Preparing for Today’s Challenges, pp. 3–17. CRC Press, Boca Raton (2014)Google Scholar
  3. 3.
    Guha-Sapir, D., Hoyois, P., Below, R.: Annual Disaster Statistical Review 2015: The Numbers and Trends. CRED, Brussels (2016)Google Scholar
  4. 4.
    Cassidy, T.: Problem-solving style, achievement motivation, psychological distress and response to a simulated emergency. Couns. Psychol. Q. 15, 325–332 (2002)CrossRefGoogle Scholar
  5. 5.
  6. 6.
    Van de Walle, B., Turoff, M.: Decision support for emergency situations. Inf. Syst. e-Bus. Manag. 6, 295–316 (2008)CrossRefGoogle Scholar
  7. 7.
    Neria, Y., Nandi, A., Galea, S.: Post-traumatic stress disorder following disasters: a systematic review. Psychol. Med. 38, 467–480 (2008)CrossRefGoogle Scholar
  8. 8.
    Aldag, R.J.: Decision making: a psychological analysis of conflict. Acad. Manag. Rev. 5, 141–143 (1980)Google Scholar
  9. 9.
    Helbing, D., Farkas, I.J., Molnar, P., Vicsek, T.: Simulation of pedestrian crowds in normal and evacuation situations. In: Schreckenberg, M., Sharma, S.D. (eds.) Pedestrian and Evacuation Dynamics, pp. 21–58. Springer, Berlin (2002)Google Scholar
  10. 10.
    Pine, J.C.: Natural Hazards Analysis: Reducing the Impact of Disasters. CRC Press, Boca Raton (2009)Google Scholar
  11. 11.
    Cocking, C., Drury, J., Reicher, S.: The psychology of crowd behaviour in emergency evacuations: results from two interview studies and implications for the fire and rescue services. Irish J. Psychol. 30, 59–73 (2009)CrossRefGoogle Scholar
  12. 12.
    Purser, D.A., Raggio, A.J.T.: Behaviour of crowds when subjected to fire intelligence. Building Research Establishing Report CR 143/95. Building Research Establishment Ltd., Watford (1995)Google Scholar
  13. 13.
    Purser, D.A., Bensilum, M.: Quantification of escape behavior during experimental evacuations. Building Research Establishment Report CR 30/99. Building Research Establishment Ltd., Watford (1999)Google Scholar
  14. 14.
    Vorst, H.C.M.: Evacuation models and disaster psychology. Procedia Eng. 3, 15–21 (2010)CrossRefGoogle Scholar
  15. 15.
    Leach, J.: Survival Psychology. Palgrave Macmillan, London (1994)CrossRefGoogle Scholar
  16. 16.
    Purser, D.A., Bensilum, M.: Quantification of behaviour for engineering design standards and escape time calculations. Saf. Sci. 38, 157–182 (2001)CrossRefGoogle Scholar
  17. 17.
    International Organization for Standardization.
  18. 18.
    Kobes, M., Helsloot, I., de Vries, B., Post, J.G., Oberijé́, N., Groenewegen, K.: Way finding during fire evacuation; an analysis of unannounced fire drills in a hotel at night. Build. Environ. 45, 537–548 (2010)CrossRefGoogle Scholar
  19. 19.
    Sime, J., Breaux, J., Canter, D.: Human Behaviour Patterns in Domestic and Hospital Fires. BRE Report, UK (1994)Google Scholar
  20. 20.
    Gwynne, S., Galea, E.R., Lawrence, P.J., Filippidis, L.: Modelling occupant interaction with fire conditions using the buildingEXODUS evacuation model. Fire Saf. J. 36, 327–357 (2001)CrossRefGoogle Scholar
  21. 21.
    Ozel, F.: Time pressure and stress as a factor during emergency egress. Saf. Sci. 38, 95–107 (2001)CrossRefGoogle Scholar
  22. 22.
    Knuth, D., Kehl, D., Hulse, L., Schmidt, S.: Perievent distress during fires-the impact of perceived emergency knowledge. J. Environ. Psychol. 34, 10–17 (2013)CrossRefGoogle Scholar
  23. 23.
    Heliovaara, S., Kuusinen, J., Rinne, T., Korhonen, T., Ehtamo, H.: Pedestrian behavior and exit selection in evacuation of a corridor-an experimental study. Saf. Sci. 50, 221–227 (2012)CrossRefGoogle Scholar
  24. 24.
    Mu, H.L., Wang, J.H., Mao, Z.L., Sun, J.H., Lo, S.M., Wang, Q.S.: Pre-evacuation human reactions in fires: an attribution analysis considering psychological process. Procedia Eng. 52, 290–296 (2013)CrossRefGoogle Scholar
  25. 25.
    Yoon, S.W., Velasquez, J.D., Partridge, B.K., Nof, S.Y.: Transportation security decision support system for emergency response: a training prototype. Decis. Support Syst. 46, 139–148 (2008)CrossRefGoogle Scholar
  26. 26.
    Ben Zur, H., Breznitz, J.S.: The effect of time pressure on risky choice behavior. Acta Physiol. 47, 89–104 (1981)Google Scholar
  27. 27.
    Gantt, P., Gantt, R.: Disaster psychology: dispelling the myths of panic. Prof. Saf. 57(8), 42–49 (2012)Google Scholar
  28. 28.
    Staw, B.M., Sandelands, L.E., Dutton, J.E.: Threat-rigidity effects in organizational behavior: a multilevel analysis. Adm. Sci. Q. 26, 501–524 (1981)CrossRefGoogle Scholar
  29. 29.
    Rice, R.E.: From adversity to diversity: applications of communication technology to crisis management. Adv. Telecommun. Manag. 3, 91–112 (1990)Google Scholar
  30. 30.
    Abolghasemzadeh, P.: A comprehensive method for environmentally sensitive and behavioral microscopic egress analysis in case of fire in buildings. Saf. Sci. 59, 1–9 (2013)CrossRefGoogle Scholar
  31. 31.
    Bode, N.W.F., Codling, E.A.: Human exit route choice in virtual crowd evacuations. Anim. Behav. 86, 347–358 (2013)CrossRefGoogle Scholar
  32. 32.
    Turner, R.H., Killian, L.M.: Collective Behaviour. Prentice-Hall, Upper Saddle River (1957)Google Scholar
  33. 33.
    Kahnemen, D., Tversky, A.: Prospect theory: an analysis of decision under risk. Econometrica 47, 263–292 (1979)CrossRefzbMATHGoogle Scholar
  34. 34.
    Pan, X., Han, C.S., Dauber, K., Law, K.H.: Human and social behavior in computational modeling and analysis of egress. Autom. Constr. 15, 448–461 (2006)CrossRefGoogle Scholar
  35. 35.
    Tucker, C.W., Schweingruber, D., McPhail, C.: Simulating arcs and rings in gatherings. Int. J. Hum. Comput. Stud. 50, 581–588 (1999)CrossRefGoogle Scholar
  36. 36.
    Aveni, A.F.: The not-so-lonely crowd: friendship groups in collective behavior. Sociometry 48, 96–99 (1977)CrossRefGoogle Scholar
  37. 37.
    McPhail, C.: The Myth of the Madding Crowd. Aldine de Gruyter, Hawthorne (1991)Google Scholar
  38. 38.
    McPhail, C., Wohlstein, R.T.: Collective locomotion as collective behavior. Am. Sociol. Rev. 51, 447–463 (1986)CrossRefGoogle Scholar
  39. 39.
    Sime, J.D.: Affiliate behaviour during escape to building exits. J. Environ. Psychol. 3, 21–41 (1983)CrossRefGoogle Scholar
  40. 40.
    Nilsson, D., Johansson, A.: Social influence during the initial phase of a fire evacuation - analysis of evacuation experiments in a cinema theatre. Fire Saf. J. 44, 71–79 (2009)CrossRefGoogle Scholar
  41. 41.
    Armfield, J.M.: Cognitive vulnerability: a model of the etiology of fear. Clin. Psychol. Rev. 26, 746–768 (2006)CrossRefGoogle Scholar
  42. 42.
    Zakaria, W., Yusof, U.K.: Modelling crowd behaviour during emergency evacuation: a proposed framework. In: 2016 International Conference on Advanced Informatics: Concepts, Theory And Application (ICAICTA) (2016)Google Scholar
  43. 43.
    Schneider, B.: The reference model SimPan - agent-based modelling of human behaviour in panic situations. In: Tenth International Conference on Computer Modeling and Simulation (2008)Google Scholar
  44. 44.
    Helbing, D., Farkas, I., Vicsek, T.: Simulating dynamical features of escape panic. Nature 407, 487–490 (2000)CrossRefGoogle Scholar
  45. 45.
    Hu, Z., Sheu, J., Xiao, L.: Post-disaster evacuation and temporary resettlement considering panic and panic spread. Transp. Res. Part B 69, 112–132 (2014)CrossRefGoogle Scholar
  46. 46.
    Blake, S.J., Galea, E.R., Westeng, H., Dixon, A.J.P.: An analysis of human behavior during the WTC disaster of 11 September 2001 based on published survivor accounts. In: 3rd International Symposium on Human Behavior in Fire, pp. 181–192. InterScience Communications, Belfast (2004)Google Scholar
  47. 47.
    Aguirre, B.E.: Commentary on “understanding mass panic and other collective responses to threat and disaster”: emergency evacuations, panic, and social psychology. Psychiatry 68, 121–129 (2005)CrossRefGoogle Scholar
  48. 48.
    Bohannon, J.: Directing the herd: crowds and the science of evacuation. Science 310, 219–221 (2005)CrossRefGoogle Scholar
  49. 49.
    Mawson, A.R.: Understanding mass panic and other collective responses to threat and disaster. Psychiatry 68, 95–113 (2005)CrossRefGoogle Scholar
  50. 50.
    Oswald, M., Lebeda, C., Schneider, U., Kirchberger, H.: Full-scale evacuation experiments in a smoke filled rail carriage-a detailed study of passenger behavior under reduced visibility. In: Waldau, N., Gattermann, P., Knoflacher, H., Schreckenberg, M. (eds.) Pedestrian and Evacuation Dynamics. Springer, Heidelberg (2005)Google Scholar
  51. 51.
    Proulx, G.: Evacuation time. In: SFPE Handbook of Fire Protection Engineering, 4th edn, pp. 3–355. National Fire Protection Association Quincy, MA (2008)Google Scholar
  52. 52.
    Benight, C.C., Harper, M.L.: Coping self-efficacy perceptions as a mediator between acute stress response and long-term distress following natural disasters. J. Trauma. Stress 15, 177–186 (2002)CrossRefGoogle Scholar
  53. 53.
    Zhan, X., Yang, L., Zhu, K., Kong, X., Rao, P., Zhang, T.: Experimental study of the impact of personality traits on occupant exit choice during building evacuation. Procedia Eng. 62, 548–553 (2013)CrossRefGoogle Scholar
  54. 54.
    Purser, D.A.: Behavioural impairment in smoke environments. Toxicology 115, 25–40 (1996)CrossRefGoogle Scholar
  55. 55.
    Proulx, G., Sime, J.D.: To prevent panic in an underground emergency, why not tell people the truth? Fire Saf. Sci. 3, 843–852 (1991)CrossRefGoogle Scholar
  56. 56.
  57. 57.
  58. 58.
    A380 successful evacuation trial. Aircr. Eng. Aerosp. Technol. 78(4) (2006)Google Scholar
  59. 59.
  60. 60.
    Penslar, R.: Protecting Human Research Subjects. National Institutes of Health, Washington DC (1933)Google Scholar
  61. 61.
    Battey, J., Jordan, E., Cox, D., Dove, W.: An action plan for mouse genomics. Nat. Genet. 21, 73–75 (1999)CrossRefGoogle Scholar
  62. 62.
    Wasserman, W.W., Palumbo, M., Thompson, W., Fickett, J.W., Lawrence, C.E.: Human-mouse genome comparisons to locate regulatory sites. Nat. Genet. 26, 225 (2000)CrossRefGoogle Scholar
  63. 63.
    Saloma, C., Perez, G.J., Tapang, G., Lim, M., Palmes-Saloma, C.: Self-organized queuing and scale-free behavior in real escape panic. Natl. Acad. Sci. U.S.A. 100, 11947–11952 (2003)CrossRefGoogle Scholar
  64. 64.
    Lin, P., Ma, J., Liu, T., Ran, T., Si, Y., Li, T.: An experimental study of the “faster-is-slower” effect using mice under panic. Phys. A: Stat. Mech. Appl. 452, 157 (2016)CrossRefGoogle Scholar
  65. 65.
    Shiwakoti, N., Sarvi, M.: Enhancing the panic escape of crowd through architectural design. Transp. Res. Part C 37, 260–267 (2013)CrossRefGoogle Scholar
  66. 66.
    Shiwakoti, N., Sarvi, M., Rose, G., Burd, M.: Animal dynamics based approach for modeling pedestrian crowd egress under panic conditions. Procedia – Soc. Behav. Sci. 17, 438–461 (2011)CrossRefGoogle Scholar
  67. 67.
    Soria, S., Josens, R., Parisi, D.: Experimental evidence of the “faster is slower” effect in the evacuation of ants. Saf. Sci. 50, 1584–1588 (2012)CrossRefGoogle Scholar
  68. 68.
    Parisi, D., Soria, S., Josens, R.: Faster-is-slower effect in escaping ants revisited: ants do not behave like humans. Saf. Sci. 72, 274–282 (2015)CrossRefGoogle Scholar
  69. 69.
    Shi, J., Ren, A., Chen, C.: Agent-based evacuation model of large public buildings under fire conditions. Autom. Constr. 18, 338–347 (2009)CrossRefGoogle Scholar
  70. 70.
    Sharma, S., Singh, H., Prakash, A.: Multi-agent modeling and simulation of human behavior in aircraft evacuation. IEEE Trans. Aerosp. Electron. Syst. 44, 1477–1499 (2008)CrossRefGoogle Scholar
  71. 71.
    Treiber, M., Hennecke, A., Helbing, D.: Derivation, properties, and simulation of a gas-kinetic-based, nonlocal traffic model. Phys. Rev. E 59(1), 239 (1999)CrossRefGoogle Scholar
  72. 72.
    Wei-Guo, S., Yan-Fei, Y., Bing-Hong, W., Wei-Cheng, F.: Evacuation behaviors at exit in ca model with force essentials: a comparison with social force model. Phys. A 371(2), 658–666 (2006)CrossRefGoogle Scholar
  73. 73.
    Li, F., Chen, S., Wang, X., Feng, F.: Pedestrian evacuation modeling and simulation on metro platforms considering panic impacts. Procedia-Soc. Behav. Sci. 138, 314–322 (2014)CrossRefGoogle Scholar
  74. 74.
    Mehran, R., Oyama, A., Shah, M.: Abnormal crowd behavior detection using social force model. In: Computer Vision and Pattern Recognition IEEE Conference, pp. 935–942. IEEE Press, New York (2009)Google Scholar
  75. 75.
    Zanlungo, F., Ikeda, T., Kanda, T.: Social force model with explicit collision prediction. EPL (Europhy. Lett.) 93(6), 68005 (2011)CrossRefGoogle Scholar
  76. 76.
    Flötteröd, G., Lämmel, G.: Bidirectional pedestrian fundamental diagram. Transp. Res. Part B: Methodol. 71, 194–212 (2015)CrossRefGoogle Scholar
  77. 77.
    Lakoba, T.I., Kaup, D.J., Finkelstein, N.M.: Modifications of the helbing-molnar-farkas-vicsek social force model for pedestrian evolution. Simulation 81, 339–352 (2005)CrossRefGoogle Scholar
  78. 78.
    Bruno, L., Venuti, F.: The pedestrian speed–density relation: modelling and application. In: 3rd Footbridge International Conference (2008)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Yixuan Cheng
    • 1
    Email author
  • Dahai Liu
    • 1
  • Jie Chen
    • 1
  • Sirish Namilae
    • 1
  • Jennifer Thropp
    • 1
  • Younho Seong
    • 2
  1. 1.Embry-Riddle Aeronautical UniversityDaytona BeachUSA
  2. 2.North Carolina Agricultural and Technical State UniversityGreensboroUSA

Personalised recommendations