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Modeling a Crowd of Groups: Multidisciplinary and Methodological Challenges

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Book cover Modeling, Simulation and Visual Analysis of Crowds

Part of the book series: The International Series in Video Computing ((VICO,volume 11))

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Abstract

The main aim of the chapter is to introduce a recent and current trend of research in the modeling, simulation and visual analysis of crowds: the study of the impact of groups on the overall crowd dynamics, and its implications of the aforementioned research activities as well as their outcomes. In most situations, in fact, a crowd of pedestrians is more than a simple set of individuals, each interpreting the presence of the others in a uniform way, trying to preserve a certain distance from the nearest person. A crowd is rather a composite assembly of individuals, some of which are bound by different types of ties, not only representing the presence of other pedestrians as a repulsive force, influencing their attitude towards the movement in the environment. Current models for the simulation of crowds of pedestrians have just started to analyze this phenomenon, and we still lack a complete understanding of the implications of not considering it, either in a real simulation project supporting decision making activities of designers or planners, or in the analysis and automatic extraction of information, for instance from video footage of events or crowded environments.

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Notes

  1. 1.

    See http://www.evacmod.net/?q=node/5 for a large although not necessarily complete list of pedestrian simulation models and tools.

References

  1. Bandini, S., Federici, M.L., Vizzari, G.: Situated cellular agents approach to crowd modeling and simulation. Cybern. Syst. 38(7), 729–753 (2007)

    Article  MATH  Google Scholar 

  2. Bandini, S., Manenti, L., Manzoni, S., Sartori, F.: A knowledge-based approach to crowd classification. In: Proceedings of the 5th International Conference on Pedestrian and Evacuation Dynamics, March 8–10, Gaithersburg, MD, USA (2010)

    Google Scholar 

  3. Bandini, S., Manzoni, S., Redaelli, S.: Towards an ontology for crowds description: a proposal based on description logic. In: Umeo, H., Morishita, S., Nishinari, K., Komatsuzaki, T., Bandini, S. (eds.) ACRI. Lecture Notes in Computer Science, vol. 5191, pp. 538–541. Springer, Berlin, Germany (2008)

    Google Scholar 

  4. Bandini, S., Manzoni, S., Vizzari, G.: Agent based modeling and simulation: an informatics perspective. J. Artif. Soc. Soc. Simul. 12(4), 4 (2009)

    Google Scholar 

  5. Bandini, S., Rubagotti, F., Vizzari, G., Shimura, K.: An agent model of pedestrian and group dynamics: experiments on group cohesion. In: Pirrone, R., Sorbello, F. (eds.) AI*IA. Lecture Notes in Computer Science, vol. 6934, pp. 104–116. Springer, Berlin, Germany (2011)

    Google Scholar 

  6. Batty, M.: Agent based pedestrian modeling (editorial). Environ. Plan. B: Plan. Des. 28, 321–326 (2001)

    Article  Google Scholar 

  7. Blue, V.J., Adler, J.L.: Cellular automata microsimulation of bi-directional pedestrian flows. Transp. Res. Rec. 1678, 135–141 (1999)

    Article  Google Scholar 

  8. Blue, V.J., Adler, J.L.: Modeling four-directional pedestrian flows. Trans. Res. Rec. 1710, 20–27 (2000)

    Article  Google Scholar 

  9. Bonomi, A., Manenti, L., Manzoni, S., Vizzari, G.: Makksim: dealing with pedestrian groups in MAS-based crowd simulation. In: Fortino, G., Garro, A., Palopoli, L., Russo, W., Spezzano, G. (eds.) WOA. CEUR Workshop Proceedings, Rende, vol. 741, pp. 166–170 (2011). http://CEUR-WS.org

  10. Canetti, E.: Crowds and power. Farrar, Straus and Giroux, New York (1984)

    Google Scholar 

  11. Challenger, R., Clegg, C.W., Robinson, M.A.: Understanding crowd behaviours: Supporting evidence. Tech. rep., University of Leeds (2009)

    Google Scholar 

  12. Chattaraj, U., Seyfried, A., Chakroborty, P.: Comparison of pedestrian fundamental diagram across cultures. Adv. Complex Syst. 12(3), 393–405 (2009)

    Article  Google Scholar 

  13. Costa, M.: Interpersonal distances in group walking. J. Nonverbal Behav. 34, 15–26 (2010). http://dx.doi.org/10.1007/s10919-009-0077-y, doi:10.1007/s10919-009-0077-y

    Google Scholar 

  14. Dijkstra, J., Jessurun, J., de Vries, B., Timmermans, H.J.P.: Agent architecture for simulating pedestrians in the built environment. In: International Workshop on Agents in Traffic and Transportation, pp. 8–15, Hakodate, Japan (2006)

    Google Scholar 

  15. Dopfer, K., Foster, J., Potts, J.: Micro-meso-macro. J. Evol. Econ. 14, 263–279 (2004). http://dx.doi.org/10.1007/s00191-004-0193-0, doi:10.1007/s00191-004-0193-0

    Google Scholar 

  16. Fabietti, U.E.M.: Gruppi – Antropologia, vol. Enciclopedia delle Scienze Sociali, pp. 424–429. Treccani (1994)

    Google Scholar 

  17. Federici, M.L., Gorrini, A., Manenti, L., Vizzari, G.: An innovative scenario for pedestrian data collection: the observation of an admission test at the university of Milano-Bicocca. In: Proceedings of the 6th International Conference on Pedestrian and Evacuation Dynamics – PED 2012, Zurich, Switzerland (2012)

    Google Scholar 

  18. Fruin, J.J.: Pedestrian planning and design. Metropolitan Association of Urban Designers and Environmental Planners, New York (1971)

    Google Scholar 

  19. Georgoudas, I.G., Sirakoulis, G.C., Andreadis, I.: An anticipative crowd management system preventing clogging in exits during pedestrian evacuation processes. IEEE Syst. J. 5(1), 129–141 (2011)

    Article  Google Scholar 

  20. Gloor, C., Stucki, P., Nagel, K.: Hybrid techniques for pedestrian simulations. In: Sloot, P.M.A., Chopard, B., Hoekstra, A.G. (eds.) 6th International Conference on Cellular Automata for Research and Industry, ACRI 2004. Lecture Notes in Computer Science, vol. 3305, pp. 581–590. Springer, Berlin, Germany (2004)

    Google Scholar 

  21. Gualdi, G., Prati, A., Cucchiara, R.: Contextual information and covariance descriptors for people surveillance: An application for safety of construction workers. EURASIP J. Image Video Process. 2011 (2011)

    Google Scholar 

  22. Hall, E.T.: A system for the notation of proxemic behavior. Am. Anthropol. 65(5), 1003–1026 (1963). http://www.jstor.org/stable/668580

  23. Hall, E.T.: The Hidden Dimension. Anchor Books, New York (1966)

    Google Scholar 

  24. Helbing, D.: A fluid–dynamic model for the movement of pedestrians. Complex Syst. 6(5), 391–415 (1992)

    MathSciNet  MATH  Google Scholar 

  25. Helbing, D., Molnár, P.: Social force model for pedestrian dynamics. Phys. Rev. E 51(5), 4282–4286 (1995)

    Article  Google Scholar 

  26. Helbing, D., Schweitzer, F., Keltsch, J., Molnár, P.: Active walker model for the formation of human and animal trail systems. Phys. Rev. E 56(3), 2527–2539 (1997)

    Article  Google Scholar 

  27. Henein, C.M., White, T.: Agent-based modelling of forces in crowds. In: Davidsson, P., Logan, B., Takadama, K. (eds.) Joint Workshop on Multi-agent and Multi-agent-based Simulation, MABS 2004, New York, 19 July 2004, Revised Selected Papers. Lecture Notes in Computer Science, vol. 3415, pp. 173–184. Springer (2005)

    Google Scholar 

  28. Junior, J.C.J., Musse, S.R., Jung, C.R.: Crowd analysis using computer vision techniques. IEEE Signal Process. Mag. 27(5), 66–77 (2010)

    Google Scholar 

  29. Kirchner, A., Schadschneider, A.: Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics. Phys. A: Stat. Mech. Appl. 312(1–2), 260–276 (2002). http://www.sciencedirect.com/science/article/pii/S0378437102008579

  30. Klüpfel, H.: A cellular automaton model for crowd movement and egress simulation. P.hd. thesis, University Duisburg-Essen (2003)

    Google Scholar 

  31. Leal-Taixé, L., Pons-Moll, G., Rosenhahn, B.: Everybody needs somebody: modeling social and grouping behavior on a linear programming multiple people tracker. In: ICCV Workshops, pp. 120–127. IEEE, Barcelona, Spain (2011)

    Google Scholar 

  32. Manenti, L., Manzoni, S., Vizzari, G., Ohtsuka, K., Shimura, K.: Towards an agent-based proxemic model for pedestrian and group dynamic. In: Omicini, A., Viroli, M. (eds.) WOA. CEUR Workshop Proceedings, vol. 621, Rimini, Italy (2010). http://CEUR-WS.org

  33. Manenti, L., Manzoni, S., Vizzari, G., Ohtsuka, K., Shimura, K.: An agent-based proxemic model for pedestrian and group dynamics: motivations and first experiments. In: Villatoro, D., Sabater-Mir, J., Sichman, J.S. (eds.) MABS. Lecture Notes in Computer Science, vol. 7124, pp. 74–89. Springer Berlin, Germany (2011)

    Google Scholar 

  34. Moussaïd, M., Perozo, N., Garnier, S., Helbing, D., Theraulaz, G.: The walking behaviour of pedestrian social groups and its impact on crowd dynamics. PLoS ONE 5(4), e10047 (2010). http://dx.doi.org/10.1371%2Fjournal.pone.0010047

  35. 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)

    Article  Google Scholar 

  36. Nagel, K., Schreckenberg, M.: A cellular automaton model for freeway traffic. Journal de Physique I France 2(2221), 222–235 (1992)

    Google Scholar 

  37. Nishinari, K., Kirchner, A., Namazi, A., Schadschneider, A.: Extended floor field ca model for evacuation dynamics. IEICE Trans. Inf. syst. 87(3), 726–732 (2004)

    Google Scholar 

  38. Nishinari, K., Suma, Y., Yanagisawa, D., Tomoeda, A., Kimura, A., Nishi, R.: Toward smooth movement of crowds. In: Pedestrian and Evacuation Dynamics 2008, pp. 293–308. Springer, Berlin/Heidelberg (2008)

    Google Scholar 

  39. Okazaki, S.: A study of pedestrian movement in architectural space, part 1: pedestrian movement by the application of magnetic models. Trans. A.I.J. 283, 111–119 (1979)

    Google Scholar 

  40. Paris, S., Donikian, S.: Activity-driven populace: A cognitive approach to crowd simulation. IEEE Comput. Graph. Appl. 29(4), 34–43 (2009)

    Article  Google Scholar 

  41. Patil, S., van den Berg, J.P., Curtis, S., Lin, M.C., Manocha, D.: Directing crowd simulations using navigation fields. IEEE Trans. Vis. Comput. Graph. 17(2), 244–254 (2011)

    Google Scholar 

  42. Qiu, F., Hu, X.: Modeling group structures in pedestrian crowd simulation. Simul. Model. Pract. Theory 18(2), 190–205 (2010)

    Article  Google Scholar 

  43. Raghavendra, R., Bue, A.D., Cristani, M., Murino, V.: Abnormal crowd behavior detection by social force optimization. In: Salah, A.A., Lepri, B. (eds.) HBU. Lecture Notes in Computer Science, vol. 7065, pp. 134–145. Springer, Berlin, Germany (2011)

    Google Scholar 

  44. Sarmady, S., Haron, F., Talib, A.Z.H.: Modeling groups of pedestrians in least effort crowd movements using cellular automata. In: Al-Dabass, D., Triweko, R., Susanto, S., Abraham, A. (eds.) Asia International Conference on Modelling and Simulation, pp. 520–525. IEEE Computer Society, Bali, Indonesia (2009)

    Google Scholar 

  45. Schadschneider, A., Kirchner, A., Nishinari, K.: CA approach to collective phenomena in pedestrian dynamics. In: Bandini, S., Chopard, B., Tomassini, M. (eds.) 5th International Conference on Cellular Automata for Research and Industry, ACRI 2002. Lecture Notes in Computer Science, vol. 2493, pp. 239–248. Springer, Berlin, Germany (2002)

    Google Scholar 

  46. Schadschneider, A., Klingsch, W., Klüpfel, H., Kretz, T., Rogsch, C., Seyfried, A.: Evacuation dynamics: empirical results, modeling and applications. In: Meyers, R.A. (ed.) Encyclopedia of Complexity and Systems Science, pp. 3142–3176. Springer, New York (2009)

    Chapter  Google Scholar 

  47. Schreckenberg, M., Sharma, S.D. (eds.): Pedestrian and Evacuation Dynamics. Springer, Berlin, Germany (2001)

    Google Scholar 

  48. Schultz, M., Schulz, C., Fricke, H.: Passenger dynamics at airport terminal environment. In: Klingsch, W.W.F., Rogsch, C., Schadschneider, A., Schreckenberg, M. (eds.) Pedestrian and Evacuation Dynamics 2008, pp. 381–396. Springer, Heidelberg/New York (2010)

    Chapter  Google Scholar 

  49. Shao, W., Terzopoulos, D.: Autonomous pedestrians. Graph. Models 69(5–6), 246–274 (2007)

    Article  Google Scholar 

  50. Toyama, M.C., Bazzan, A.L.C., da Silva, R.: An agent-based simulation of pedestrian dynamics: from lane formation to auditorium evacuation. In: Nakashima, H., Wellman, M.P., Weiss, G., Stone, P. (eds.) 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), pp. 108–110. ACM, Hakodate, Japan (2006)

    Google Scholar 

  51. Was, J.: Crowd dynamics modeling in the light of proxemic theories. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC (2). Lecture Notes in Computer Science, vol. 6114, pp. 683–688. Springer, Berlin, Germany (2010)

    Google Scholar 

  52. Willis, A., Gjersoe, N., Havard, C., Kerridge, J., Kukla, R.: Human movement behaviour in urban spaces: implications for the design and modelling of effective pedestrian environments. Environ. Plan. B 31(6), 805–828 (2004)

    Article  Google Scholar 

  53. Xu, S., Duh, H.B.L.: A simulation of bonding effects and their impacts on pedestrian dynamics. IEEE Trans. Intell. Transp. Syst. 11(1), 153–161 (2010)

    Article  Google Scholar 

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Acknowledgements

This work is a result of the Crystal Project, funded by the Center of Research Excellence in Hajj and Omrah (Hajjcore), Umm Al-Qura University, Makkah, Saudi Arabia. Our acknowledgement for the common work in the project and for fruitful discussions goes to Katsuhiro Nishinari (RCAST – Research Center for Advanced Science and Technology, The University of Tokyo, Japan), our valuable partner within the Crystals Project. We also thank Ugo Fabietti (CREAM – University of Milano-Bicocca) for his contribution from the area of Anthropology.

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Authors and Affiliations

  1. Department of Computer Science, Systems and Communication, Complex Systems and Artificial Intelligence (CSAI) Research Center, University of Milan – Bicocca, Viale Sarca 336/14, 20126, Milano, Italy

    Stefania Bandini & Giuseppe Vizzari

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  1. Stefania Bandini
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  2. Giuseppe Vizzari
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Correspondence to Stefania Bandini .

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Editors and Affiliations

  1. Center for Vision Technologies, SRI International, Princeton, New Jersey, USA

    Saad Ali

  2. Department of Computer Science, Drexel University, Philadelphia, Pennsylvania, USA

    Ko Nishino

  3. Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina, USA

    Dinesh Manocha

  4. Center for Research in Computer Vision, University of Central Florida, Orlando, Florida, USA

    Mubarak Shah

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Bandini, S., Vizzari, G. (2013). Modeling a Crowd of Groups: Multidisciplinary and Methodological Challenges. In: Ali, S., Nishino, K., Manocha, D., Shah, M. (eds) Modeling, Simulation and Visual Analysis of Crowds. The International Series in Video Computing, vol 11. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8483-7_5

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