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Analysis of an efficient rule-based motion planning system for simulating human crowds

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Abstract

This paper proposes a rule-based motion planning system for agent-based crowd simulation, consisting of sets of rules for both collision avoidance and collision response. In order to avoid an oncoming collision, a set of rules for velocity sampling and evaluation is proposed, which aims to choose a velocity with an expected time to collision larger than a predefined threshold. In order to improve the efficiency over existing methods, the sampling procedure terminates upon finding an appropriate velocity. Moreover, the proposed motion planning system does not guarantee a collision-free movement. In case of collision, another set of rules is also defined to direct the agent to make a corresponding response. The experiment results show that the proposed approach can be applied in different scenarios, while making the simulation execution efficient.

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References

  1. http://www.cs.unc.edu/~geom/RVO/Library/ (Accessed December 2009)

  2. Abe, Y., Yoshiki, M.: Collision avoidance method for multiple autonomous mobile agents by implicit cooperation. In: Proceedings of 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1207–1212 (2001)

  3. van den Berg, J., Lin, M., Manocha, D.: Reciprocal velocity obstacles for real-time multi-agent navigation. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 1928–1935 (2008)

  4. van den Berg, J., Overmars, M.: Planning time-minimal safe paths amidst unpredictably moving obstacles. Int. J. Robotics Res. 27(11–12), 1274–1294 (2008)

    Google Scholar 

  5. van den Berg, J., Patil, S., Sewall, J., Manocha, D., Lin, M.: Interactive navigation of individual agents in crowded environments. In: Proceedings of Symposium on Interactive 3D Graphics and Games (I3D’08), pp. 139–147 (2008)

  6. Boris, K., Erwin, P.: Reflective navigation: Individual behaviors and: group behaviors. In: Proceedings of 2004 IEEE International Conference on Robotics and Automation, pp. 4172–4177 (2004)

  7. Feurtey, F.: Simulating the collision avoidance behavior of pedestrians. Master’s thesis, University of Tokyo (2000)

  8. Fiorini, P., Shiller, Z.: Motion planning in dynamic environments using velocity obstacles. Int. J. Robotics Res. 17(7), 23–33 (1998)

    Google Scholar 

  9. Fox, D., Burgard, W., Thrun, S.: The dynamic window approach to collision avoidance. IEEE Robotics Autom. Mag. 4(1), 23–33 (1997)

    Article  Google Scholar 

  10. Gayle, R., Sud, A., Lin, M., Manocha, D.: Reactive deforming roadmaps: Motion planning of multiple robots in dynamic environments. Int. J. Robotics Res. 21(3), 233–255 (2002)

    Article  Google Scholar 

  11. Helbing, D., Farkás, I.J., Molnár, 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 

  12. Hsu, D., Kindel, R., Latombe, J.C., Rock, S.: Randomized kinodynamic motion planning with moving obstacles. Int. J. Robotics Res. 21(3), 233–255 (2002)

    Article  Google Scholar 

  13. Hughes, R.: A continuum theory for the flow of pedestrians. Transp. Res. Part B 36(6), 507–535 (2002)

    Article  Google Scholar 

  14. Jaillet, L., Simeon, T.: A PRM-based motion planner for dynamically changing environments. In: Proceedings of IEEE/RSJ Int. Conference on Intelligent Robots and Systems, pp. 1606–1611 (2004)

  15. Li, Y., Gupta, K.: Motion planning of multiple agents in virtual environments on parallel architectures. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 1009–1014 (2007)

  16. Mazarakis, G.P., Avaritsiotis, J.N.: A prototype sensor node for footstep detection. In: Wireless Sensor Networks, 2005. Proceedings of the Second European Workshop, pp. 415–418 (2005)

  17. Nguyen, Q.H., McKenzie, F.D., Petty, M.D.: Crowd behavior cognitive model architecture design. In: Proceedings of the 2005 Behavior Representation in Modeling and Simulation (BRIMS) Conference, pp. 55–64. Universal City, CA (2005)

  18. Parisi, D.R., Dorso, C.O.: Why faster is slower in evacuation process. In: Waldau, N., Gattermann, P., Knoflacher, H., Schreckenberg, M. (eds.) Pedestrian and Evacuation Dynamics 2005, pp. 341–346 (2007)

  19. Pelechano, N., Allbeck, J., Badler, N.: Controlling individual agents in high-density crowd simulation. In: ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA’07), pp. 99–108 (2007)

  20. Pelechano, N., Allbeck, J., Badler, N.I.: Virtual Crowds: Methods, Simulation, and Control. Morgan & Claypool (2008)

  21. Pelechano, N., O’Brien, K., Silverman, B., Badler, N.: Crowd simulation incorporating agent psychological models, roles and communication. In: Proceedings of the First International Workshop on Crowd Simulation. EPFL, Lausanne, Switzerland (2005)

  22. Shiller, Z., Large, F., Sekhavat, S.: Motion planning in dynamic environments: Obstacles moving along arbitrary trajectories. In: Proceedings of IEEE International Conference on Robotics and Automation, vol. 4, pp. 3716–3721 (2001)

  23. Stephen, C.: Flow tiles. In: Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer Animation, pp. 233–242. San Diego, California, USA (2004)

  24. Sud, A., Andersen, E., Curtis, S., Lin, M., Manocha, D.: Real-time path planning for virtual agents in dynamic environments. In: Proceedings of IEEE Virtual Reality, pp. 91–98 (2007)

  25. Thalmann, D., Musse, S.: Crowd Simulation. Springer, Berlin (2007)

    Google Scholar 

  26. Treuille, A., Cooper, S., Popović, Z.: Continuum crowds. In: Proceedings of ACM SIGGRAPH, pp. 1160–1168 (2006)

  27. Weng, W., Pan, L., Shen, S., Yuan, H.: Small-grid analysis of discrete model for evacuation from a hall. Phys. A: Stat. Mech. Appl. 374(2), 821–826 (2007)

    Article  Google Scholar 

  28. Xiong, M., Lees, M., Cai, W., Zhou, S., Low, M.Y.H.: A rule-based motion planning for crowd simulation. In: 2009 International Conference on CyberWorlds, pp. 88–95 (2009)

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Correspondence to Muzhou Xiong.

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This paper is an extended version of our paper titled “A Rule-Based Motion Planning for Crowd Simulation” that appeared in the proceedings of 2009 International Conference on Cyberworlds (Cyberworlds 2009), pp. 88–95.

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Xiong, M., Lees, M., Cai, W. et al. Analysis of an efficient rule-based motion planning system for simulating human crowds. Vis Comput 26, 367–383 (2010). https://doi.org/10.1007/s00371-010-0421-6

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