Aggregate Dynamics for Dense Crowd Simulation

Rahul Narain     Abhinav Golas     Sean Curtis     Ming Lin
University of North Carolina at Chapel Hill

Abstract

Large dense crowds show aggregate behavior with reduced individual freedom of movement. We present a novel, scalable approach for simulating such crowds, using a dual representation both as discrete agents and as a single continuous system. In the continuous setting, we introduce a novel variational constraint called unilateral incompressibility, to model the large-scale behavior of the crowd, and accelerate inter-agent collision avoidance in dense scenarios. This approach makes it possible to simulate very large, dense crowds composed of up to a hundred thousand agents at near interactive rates on desktop computers.

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Last updated: 17 Nov 2009