Encyclopedia of Computer Graphics and Games

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Crowd Evacuation Using Simulation Techniques

  • Sai-Keung WongEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-08234-9_104-1



Crowd Evacuation Simulation: Using simulation techniques to simulate the motion of crowds in evacuation in virtual environments.


Crowd evacuation is important in building design, road infrastructure design, and city planning. A wide range of techniques have been proposed for crowd evacuation. The major aims of the studies on crowd evacuation include: (1) simulating the individual and crowd behaviors, (2) identifying the potential problems of building structures, (3) the effects of obstacles and exits, (4) optimal route computation. In an emergency evacuation, uncontrolled actions are observable in a massive crowd due to the influences of individuals. However, there are ethical issues to perform real life experiments. Therefore, using mathematical models and computer simulations are essential in studying crowd evacuation. The major goal of crowd...

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  1. Abdelghany, A., Abdelghany, K., Mahmassani, H., Alhalabi, W.: Modeling framework for optimal evacuation of large-scale crowded pedestrian facilities. Eur. J. Oper. Res. 237(3), 1105–1118 (2014)MathSciNetCrossRefzbMATHGoogle Scholar
  2. Berseth, G., Usman, M., Haworth, B., Kapadia, M., Faloutsos, P.: Environment optimization for crowd evacuation. Comput. Anim. Virtual. Worlds. 26(3–4), 377–386 (2015)CrossRefGoogle Scholar
  3. Boatright, C.D., Kapadia, M., Shapira, J.M., Badler, N.I.: Generating a multiplicity of policies for agent steering in crowd simulation. Comput. Anim. Virtual. Worlds. 26(5), 483–494 (2015)CrossRefGoogle Scholar
  4. Curtis, S., Zafar, B., Gutub, A., Manocha, D.: Right of way. Vis. Comput. 29(12), 1277–1292 (2013)CrossRefGoogle Scholar
  5. Desmet, A., Gelenbe, E.: Capacity based evacuation with dynamic exit signs. In: Pervasive Computing and Communications Workshops (PERCOM Workshops), 2014 I.E. International Conference, pp. 332–337 (2014)Google Scholar
  6. Dimakis, N., Filippoupolitis, A., Gelenbe, E.: Distributed building evacuation simulator for smart emergency management. Comput. J. 53(9), 1384–1400 (2009)CrossRefGoogle Scholar
  7. Dressler, D., Groß, M., Kappmeier, J.P., Kelter, T., Kulbatzki, J., Plmpe, D., Schlechter, G., Schmidt, M., Skutella, M., Temme, S.: On the use of network flow techniques for assigning evacuees to exits. Proc. Eng. 3, 205–215 (2010)CrossRefGoogle Scholar
  8. Funda Durupınar, Uğur Güdükbay, Aytek Aman, Norman I. Badler. IEEE Transactions on Visualization and Computer Graphics (Volume: 22, Issue: 9, Sept. 1 2016), pp. 2145–2159.Google Scholar
  9. Fu-Shun Li, Sai-Keung Wong: Animating agents based on radial view in crowd simulation. In: Proceedings of the 22nd ACM Conference on Virtual Reality Software and Technology, pp. 101–109 (2016)Google Scholar
  10. Guy, S.J., Chhugani, J., Curtis, S., Dubey, P., Lin, M., Manocha, D.: Pledestrians: A least-effort approach to crowd simulation. In: Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 119–128 (2010)Google Scholar
  11. Hadzic, T., Brown, K.N., Sreenan, C.J.: Real-time pedestrian evacuation planning during emergency. In: Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference, pp. 597–604 (2011)Google Scholar
  12. Hai-Rong Wang, Qing-Guang Chen, Jian-Bo Yan, Zhi Yuan, Dong Liang: Emergency guidance evacuation in fire scene based on pathfinder. In: Proceedings of the 2014 7th International Conference on Intelligent Computation Technology and Automation, pp. 226–230 (2014)Google Scholar
  13. Hamacher, H.W., Tjandra, S.A.: Mathematical modelling of evacuation problems – A state of the art. In: Pedestrian and Evacuation Dynamics, Springer, Berlin, pp. 227–266 (2002).Google Scholar
  14. Helbing, D., Molnar, P.: Social force model for pedestrian dynamics. Phys. Rev. E. 51, 4282–4286 (1995)CrossRefGoogle Scholar
  15. Hughes, R.L.: A continuum theory for the flow of pedestrians. Transp. Res. B Methodol. 36(6), 507–535 (2002)CrossRefGoogle Scholar
  16. Hughes, R.L.: The flow of human crowds. Annu. Rev. Fluid. Mech. 35, 16982 (2003)MathSciNetCrossRefGoogle Scholar
  17. Inoue, Y., Sashima, A., Ikeda, T., Kurumatani, K.: Indoor emergency evacuation service on autonomous navigation system using mobile phone. In: Universal Communication, 2008. ISUC ’08. Second International Symposium, pp. 79–85 (2008)Google Scholar
  18. Jinghui Zhong, Wentong Cai, Linbo Luo: Crowd evacuation planning using cartesian genetic programming and agent-based crowd modeling. In: Proceedings of the 2015 Winter Simulation Conference, pp. 127–138 (2015)Google Scholar
  19. Johansson, A., Helbing, D., Shukla, P.K.: Specification of the social force pedestrian model by evolutionary adjustment to video tracking data. Adv. Complex Syst. 10(Suppl 02), 271–288 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  20. Kang Hoon Lee, Myung Geol Choi, Qyoun Hong, Jehee Lee: Group behavior from video: A data-driven approach to crowd simulation. In: Proceedings of the 2007 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 109–118 (2007)Google Scholar
  21. Kapadia, M., Pelechano, N., Allbeck, J.: Virtual Crowds: Steps Toward Behavioral Realism. Morgan & Claypool Publishers, San Rafael (2015)Google Scholar
  22. Karamouzas, I., Heil, P., van Beek, P., Overmars, M.H.: A predictive collision avoidance model for pedestrian simulation. In: Motion in Games, Lecture Notes in Computer Science, pp. 41–52. Springer, Berlin (2009)Google Scholar
  23. Lerner, A., Chrysanthou, Y., Shamir, A., Cohen-Or, D.: Data driven evaluation of crowds. In: Proceedings of the 2nd International Workshop on Motion in Games, pp. 75–83 (2009)Google Scholar
  24. Musse, S.R., Thalmann, D.: Hierarchical model for real time simulation of virtual human crowds. IEEE Trans. Vis. Comput. Graph. 7(2), 152–164 (2001)CrossRefGoogle Scholar
  25. Pelechano, N., Badler, N.I.: Modeling crowd and trained leader behavior during building evacuation. IEEE Comput. Graph. Appl. 26(6), 80–86 (2006)CrossRefGoogle Scholar
  26. Pelechano, N., Allbeck, J.M., Badler, N.I.: Controlling individual agents in high-density crowd simulation. In: Proceedings of the 2007 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 99–108 (2007)Google Scholar
  27. Rodriguez, S., Amato, N.M.: Behavior-based evacuation planning. In: Robotics and Automation (ICRA), 2010 I.E. International Conference, pp. 350–355 (2010)Google Scholar
  28. Sadiyoko, A., Riyanto, T. B., Mutijarsa, K.: The propagation of psychological variables in crowd: Simulation results. In: 2012 Sixth Asia Modelling Symposium, pp. 59–64 (2012)Google Scholar
  29. Sai-Keung Wong, Yu-Shuen Wang, Pao-Kun Tang, Tsung-Yu Tsai: Optimized Route for Crowd Evacuation. In: Pacific Graphics Short Papers pp. 7–11 (2016)Google Scholar
  30. Sai-Keung Wong, Yu-Shuen Wang, Pao-Kun Tang, Tsung-Yu Tsai: Optimized evacuation route based on crowd simulation. Comput. Vis. Media. 3(3), 243–261 (2017)CrossRefGoogle Scholar
  31. Sakour, I., Huosheng, H.: Robot-assisted crowd evacuation under emergency situations: A survey. Robotics. 6(2), (2017)Google Scholar
  32. Tang, H., Elalouf, A., Levner, E., Cheng, T.C.E.: Efficient computation of evacuation routes on a three-dimensional geometric network. Comput. Ind. Eng. 76, 231–242 (2014)CrossRefGoogle Scholar
  33. Thompson, P.A., Marchant, E.W.: A computer model for the evacuation of large building populations. Fire. Saf. J. 24(2), 131–148 (1995)CrossRefGoogle Scholar
  34. Tsai, J., Fridman, N., Bowring, E., Brown, M., Epstein, S., Kaminka, G., Marsella, S., Ogden, A., Rika, I., Sheel, A., et al.: Escapes: Evacuation simulation with children, authorities, parents, emotions, and social comparison. In: The 10th International Conference on Autonomous Agents and Multiagent Systems – vol. 2, pp. 457–464 (2011)Google Scholar
  35. Tsung-Yu Tsai, Sai-Keung Wong, Yi-Hung Chou, Guan-Wen Lin: Directing virtual crowds based on dynamic adjustment of navigation fields. Comput Anim Virtual Worlds, pp. 7–11 (2017)Google Scholar
  36. Van den Berg, J., Lin, M., and Manocha, D.: Reciprocal velocity obstacles for real-time multi-agent navigation. In: Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on Robotics and Automation, pp. 1928–1935. Pasadena, IEEE (2008)Google Scholar
  37. Wong, S.-K., Tang, P.-K., Li, F.-S., Wang, Z.-M., Yu, S.-T.: Guidance path scheduling using particle swarm optimization in crowd simulation. Comput. Animat. Virtual Worlds. 26(3–4), 387–395 (2015)CrossRefGoogle Scholar
  38. Yang, L., Zhu, K., Liu, S. Cellular automata evacuation model considering information transfer in building with obstacles. In: Peacock, R.D., Kuligowski, E.D., Averill, J.D. (eds). Pedestrain Dynamics and Evacuation. Springer, Berlin 2010Google Scholar
  39. Yi Ma, Kwok Kit Yuen, Wai Ming Lee: Effective leadership for crowd evacuation. Physica A Stat. Mech. Appl. 450, 333–341 (2016)CrossRefGoogle Scholar
  40. Zheng, X., Cheng, Y.: Modeling cooperative and competitive behaviors in emergency evacuation: A game-theoretical approach. Comput. Math. Appl. 62(12), 4627–4634 (2011)MathSciNetCrossRefzbMATHGoogle Scholar

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© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.National Chiao Tung UniversityHsinchuTaiwan