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Controlling individual agents in high-density crowd simulation

Published: 03 August 2007 Publication History

Abstract

Simulating the motion of realistic, large, dense crowds of autonomous agents is still a challenge for the computer graphics community. Typical approaches either resemble particle simulations (where agents lack orientation controls) or are conservative in the range of human motion possible (agents lack psychological state and aren't allowed to 'push' each other). Our HiDAC system (for High-Density Autonomous Crowds) focuses on the problem of simulating the local motion and global wayfinding behaviors of crowds moving in a natural manner within dynamically changing virtual environments. By applying a combination of psychological and geometrical rules with a social and physical forces model, HiDAC exhibits a wide variety of emergent behaviors from agent line formation to pushing behavior and its consequences; relative to the current situation, personalities of the individuals and perceived social density.

References

[1]
{BLA02} Bayazit, O. B., Lien, J.-M. and Amato, N. M., Roadmap-based flocking for complex environments. in Proceedings of Pacific Conference on Computer Graphics and Applications, (2002), 104--113.
[2]
{BNT94} Boulic, R., Noser, H. and Thalmann, D., Automatic derivation of curved human walking trajectories from synthetic vision. in Proceedings of Computer Animation, (1994), IEEE Computer Society Press, 93--103.
[3]
{BMO*03} Braun, A., Musse, S. R., Oliveira, L. P. L. and Bodmann, B. E. J., Modeling Individual Behaviors in Crowd Simulation. in Proceedings of Computer Animation and Social Agents, (2003), 143--148.
[4]
{BH97} Brogan, D. and Hodgins, J. Group Behaviors for Systems with Significant Dynamics. Autonomous Robots, 4, 1997. 137--153.
[5]
{Che04} Chenney, S., Flow Tiles. in ACM SIGGRAPH/ Eurographics Proceedings of Symposium on Computer Animation, (2004), 233--242.
[6]
{FBT99} Farenc, N., Boulic, R. and Thalmann, D., An informed environment dedicated to the simulation of virtual humans in urban context. in Proceedings of Eurographics, (1999), 309--318.
[7]
{HBJ*05} Helbing, Buzna, Johansson and Werner Self-Organized Pedestrian Crowd Dynamics. Transportation Science, 39 (1), 2005. 1--24.
[8]
{HFV00} Helbing, D., Farkas, I. and Vicsek, T. Simulating dynamical features of escape panic. Nature, 407, 2000. 487--490.
[9]
{KSL*96} Kavraki, L., Svestka, P., Latombe, J. and Overmars, M. Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transaction on Robotics and Automation, 12 (4), 1996. 566--580.
[10]
{KNN03} Kirchner, A., Namazi, A., Nishinari, K. and Schadschneider, A., Role of Conflicts in the Floor Field Cellular Automaton Model for Pedestrian Dynamics. in 2nd International Conference on Pedestrians and Evacuation Dynamics, (2003), 51--62.
[11]
{LKF05} Lakoba, Kaup and Finkelstein Modification of the Helbing-Molnar-Farkas-Vicsek Social Force Model for Pedestrian Evolution. Simulation, 81 (5), 2005. 339--352.
[12]
{LCC06} Lerner, A., Chrysanthou, Y. and Cohen-OR, D., Efficient cells-and-portals partitioning. in Computer Animation & Virtual Worlds, (2006), Wiley, 21--40.
[13]
{LMM03} Loscos, C., Marchal, D. and Meyer, A. Intuitive crowd behaviour in dense urban environments using local laws. IEEE Theory and Practice of Computer Graphics, 2003. 122.
[14]
{MS05} Massive_Software_Inc. 3D animation system for crowd-related visual effects, http://www.massivesoftware.com, 2005.
[15]
{OCV*02} O'Sullivan, C., Cassell, J., Vilhjalmsson, H., Dobbyn, S., Peters, C., Leeson, W., Giang, T. and Dingliana, J., Crowd and Group Simulation with Levels of Detail for Geometry, Motion and Behavior. in Third Irish Workshop on Computer Graphics, (2002).
[16]
{PHL05} Pan, X., Han, C. S. and Law, K. H., A Multi-agent Based Simulation Framework for the Study of Human and Social Behavior in Egress Analysis. in The International Conference on Computing in Civil Engineering, (Cancun, 2005).
[17]
{PB06} Pelechano, N. and Badler, N. Modeling Crowd and Trained Leader Behavior during Building Evacuation. IEEE Computer Graphics and Applications, 26 (6), 2006. 80--86.
[18]
{POS05} Pelechano, N., O'Brien, K., Silverman, B. and Badler, N., Crowd Simulation Incorporating Agent Psychological Models, Roles and Communication. in First International Workshop on Crowd Simulation. (V-CROWDS '05), (2005).
[19]
{PLT05} Pettre, J., Laumond, J.-P. and Thalmann, D., A Navigation Graph for real-time crowd animation on multilayered and uneven terrain, in First International Workshop on Crowd Simulation, (2005), 81--90.
[20]
{Rey87} R, C., Flocks, herds, and schools: A distributed behavior model. in Proceedings of ACM SIGGRAPH, (1987), 25--34.
[21]
{Rey99} Reynolds, C., Steering behaviors for autonomous characters. in Game Developers Conference, (1999), 763--782.
[22]
{ST05} Shao, W. and Terzopoulos, D., Autonomous pedestrians. in Proceedings of ACM SIGGRAPH / Eurographics Symposium on Computer Animation, (2005), 19--28.
[23]
{SBC*06} Silverman, B., Bharathy, G., Cornwell, J. and O'Brien, K. Human Behavior Models for Agents in Simulators and Games: Part II - Gamebots for a Foreign Culture. Presence, 15 (2), 2006. 163--185.
[24]
{SKG05} Sung, M., Kovar, L. and Gleicher, M., Fast and accurate goal-directed motion synthesis for crowds. in Symposium on Computer Animation, (2005), 291--300.
[25]
{TLC*01} Tecchia, F., Loscos, C., Conroy, R. and Chrysanthou, Y., Agent behavior simulator (ABS): A platform for urban behavior development, in Proceedings of ACM/EG Games Technology Conference, (2001).
[26]
{TMK99} Thalmann, D., Musse, S. R. and Kallmann, M., Virtual Humans' Behavior: Individuals, Groups, and Crowds. in Proceedings of Digital Media Futures, (1999), 13--15.
[27]
{TD00} Thomas, G. and Donikian, S., Virtual Humans Animation in Informed Urban Environments. in Proceedings of Computer Animation, (2000), 112.
[28]
{TCP06} Treuille, A., Cooper, S. and Popivic, Z., Continuum Crowds. in ACM Transactions on Graphics (SIGGRAPH 2006), (2006), 1160--1168.
[29]
{TT94} Tu, X. and Terzopoulos, D., Artificial Fishes: Physics, Locomotion, Perception, Behavior. in Proceedings of ACM SIGGRAPH, (1994), 43--50.

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cover image ACM Conferences
SCA '07: Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
August 2007
287 pages
ISBN:9781595936240

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Eurographics Association

Goslar, Germany

Publication History

Published: 03 August 2007

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SCA '07 Paper Acceptance Rate 28 of 81 submissions, 35%;
Overall Acceptance Rate 183 of 487 submissions, 38%

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  • (2019)Agent-Environment Interactions in Large-Scale Multi-Agent Based Simulation SystemsProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331767(763-771)Online publication date: 8-May-2019
  • (2018)Efficient Reciprocal Collision Avoidance between Heterogeneous Agents Using CTMATProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3237853(1044-1052)Online publication date: 9-Jul-2018
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