Scalable Behaviors for Crowd Simulation

Crowd simulation for virtual environments offers many challenges centered on the trade-offs between rich behavior, control and computational cost. In this paper we present a new approach to controlling the behavior of agents in a crowd. Our method is scalable in the sense that increasingly complex crowd behaviors can be created without a corresponding increase in the complexity of the agents. Our approach is also more authorable; users can dynamically specify which crowd behaviors happen in various parts of an environment. Finally, the character motion produced by our system is visually convincing. We achieve our aims with a situation-based control structure. Basic agents have very limited behaviors. As they enter new situations, additional, situation-specific behaviors are composed on the fly to enable agents to respond appropriately. The composition is done using a probabilistic mechanism. We demonstrate our system with three environments including a city street and a theater.