The Visual Computer

, Volume 24, Issue 10, pp 859–870 | Cite as

Real-time crowd motion planning

Scalable Avoidance and Group Behavior
  • Barbara Yersin
  • Jonathan Maïm
  • Fiorenzo Morini
  • Daniel Thalmann
Original Article


Real-time crowd motion planning requires fast, realistic methods for path planning as well as obstacle avoidance. In a previous work (Morini et al. in Cyberworlds International Conference, pp. 144–151, 2007), we introduced a hybrid architecture to handle real-time motion planning of thousands of pedestrians. In this article, we present an extended version of our architecture, introducing two new features: an improved short-term collision avoidance algorithm, and simple efficient group behavior for crowds. Our approach allows the use of several motion planning algorithms of different precision for regions of varied interest. Pedestrian motion continuity is ensured when switching between such algorithms. To assess our architecture, several performance tests have been conducted, as well as a subjective test demonstrating the impact of using groups. Our results show that the architecture can plan motion in real time for several thousands of characters.


Crowds Real-time Motion planning Groups 


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  1. 1.
    Bayazit, O.B., Lien, J.M., Amato, N.M.: Better group behaviors in complex environments using global roadmaps. In: ICAL 2003, pp. 362–370 (2003) Google Scholar
  2. 2.
    Chenney, S.: Flow tiles. In: SCA’04, pp. 233–242 (2004) Google Scholar
  3. 3.
    de Heras Ciechomski, P., Schertenleib, S., Maïm, J., Maupu, D., Thalmann, D.: Real-time shader rendering for crowds in virtual heritage. In: VAST’05, pp. 1–8 (2005) Google Scholar
  4. 4.
    Heïgeas, L., Luciani, A., Thollot, J., Castagné, N.: A physically-based particle model of emergent crowd behaviors. In: Graphicon (2003) Google Scholar
  5. 5.
    Helbing, D., Molnár, P., Schweitzer, F.: Computer simulations of pedestrian dynamics and trail formation. In: Evolution of Natural Structures, pp. 229–234 (1994) Google Scholar
  6. 6.
    Helbing, D., Farkas, I., Vicsek, T.: Simulating dynamical features of escape panic. Nature 407(6803), 487–490 (2000) CrossRefGoogle Scholar
  7. 7.
    Hughes, R.L.: A continuum theory for the flow of pedestrians. Transp. Res. Part B Methodol. 36(29), 507–535 (2002) CrossRefGoogle Scholar
  8. 8.
    Hughes, R.L.: The flow of human crowds. Annu. Rev. Fluid Mech. 35(1), 169–182 (2003) CrossRefGoogle Scholar
  9. 9.
    Kamphuis, A., Overmars, M.H.: Finding paths for coherent groups using clearance. In: SCA’04, pp. 19–28 (2004) Google Scholar
  10. 10.
    Kirchner, A., Shadschneider, A.: Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics. Physica A 312(1–2), 260–276 (2002) MATHCrossRefGoogle Scholar
  11. 11.
    Lamarche, F., Donikian, S.: Crowd of virtual humans: a new approach for real time navigation in complex and structured environments. Comput. Graph. Forum 23(3), 509–518 (2004) CrossRefGoogle Scholar
  12. 12.
    Lau, M., Kuffner, J.J.: Precomputed search trees: Planning for interactive goal-driven animation. In: SCA’06, pp. 299–308 (2006) Google Scholar
  13. 13.
    Lee, K.H., Choi, M.G., Hong, Q., Lee, J.: Group behavior from video: A data-driven approach to crowd simulation. In: SCA’07 (2007) Google Scholar
  14. 14.
    Loscos, C., Marchal, D., Meyer, A.: Intuitive crowd behaviour in dense urban environments using local laws. In: TPCG’03, p. 122 (2003) Google Scholar
  15. 15.
    Metoyer, R.A., Hodgins, J.K.: Reactive pedestrian path following from examples. In: CASA’03, p. 149 (2003) Google Scholar
  16. 16.
    Morini, F., Yersin, B., Maïm, J., Thalmann, D.: Real-time scalable motion planning for crowds. In: Cyberworlds International Conference, pp. 144–151 (2007) Google Scholar
  17. 17.
    Musse, S.R., Thalmann, D.: A model of human crowd behavior: Group inter-relationship and collision detection analysis. In: Eurographics Workshop on Computer Animation and Simulation (1997) Google Scholar
  18. 18.
    Niederberger, C., Gross, M.H.: Hierarchical and heterogeneous reactive agents for real-time applications. Comput. Graph. Forum 22(3), 323–331 (2003) CrossRefGoogle Scholar
  19. 19.
    Paris, S., Pettré, J., Donikian, S.: Pedestrian steering for crowd simulation: A predictive approach. In: Eurographics’07 (2007) Google Scholar
  20. 20.
    Pelechano, N., Allbeck, J., Badler, N.: Controlling individual agents in high-density crowd simulation. In: SCA’07 (2007) Google Scholar
  21. 21.
    Pettré, J., de Heras Ciechomski, P., Maïm, J., Yersin, B., Laumond, J.P., Thalmann, D.: Real-time navigating crowds: scalable simulation and rendering. J. Vis. Comput. Animat. 17(3–4), 445–455 (2006) Google Scholar
  22. 22.
    Pettré, J., Grillon, H., Thalmann, D.: Crowds of moving objects: Navigation planning and simulation. In: ICRA’07 (2007) Google Scholar
  23. 23.
    Reynolds, C.W.: Flocks, herds and schools: A distributed behavioral model. In: SIGGRAPH’87, pp. 25–34 (1987). DOI:
  24. 24.
    Reynolds, C.: Steering behaviors for autonomous characters (1999) Google Scholar
  25. 25.
    Reynolds, C.: Big fast crowds on ps3. In: Sandbox’06: Proceedings of the 2006 ACM SIGGRAPH Symposium on Videogames, pp. 113–121 (2006) Google Scholar
  26. 26.
    Shao, W., Terzopoulos, D.: Autonomous pedestrians. In: SCA’05, New York, NY, USA, pp. 19–28 (2005) Google Scholar
  27. 27.
    Sung, M., Gleicher, M., Chenney, S.: Scalable behaviors for crowd simulation. Comput. Graph. Forum 23(3), 519–528 (2004) CrossRefGoogle Scholar
  28. 28.
    Sung, M., Kovar, L., Gleicher, M.: Fast and accurate goal-directed motion synthesis for crowds. In: SCA’05, pp. 291–300 (2005) Google Scholar
  29. 29.
    Treuille, A., Cooper, S., Popovic, Z.: Continuum crowds. In: SIGGRAPH’06, pp. 1160–1168 (2006). DOI:

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Barbara Yersin
    • 1
  • Jonathan Maïm
    • 1
  • Fiorenzo Morini
    • 1
  • Daniel Thalmann
    • 1
  1. 1.IC ISIM VRLABLausanneSwitzerland

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