Position-Based Multi-Agent Dynamics for Real-Time Crowd Simulation

Abstract

Exploiting the e ciency and stability of Position-Based Dynamics (PBD), we introduce a novel crowd simulation method that runs at interactive rates for hundreds of thousands of agents. Our method enables the detailed modeling of per-agent behavior in a Lagrangian formulation. We model short-range and long-range collision avoidance constraints to simulate both sparse and dense crowds. The local short-range interaction is represented with collision and frictional contact between agents, as in the discrete simulation of granular materials.We incorporate a cohesion model for modeling collective behaviors and propose a new constraint for dealing with potential future collisions. Our new real-time crowd simulation method is suitable for use in interactive games.