A Distributed Framework for Scalable Large-Scale Crowd Simulation

Emerging applications in the area of Emergency Response and Disaster Management are increasingly demanding interactive capabilities to allow for the quick understanding of a critical situation, in particular in urban environments. A key component of these interactive simulations is how to recreate the behavior of a crowd in real- time while supporting individual behaviors. Crowds can often be unpredictable and present mixed behaviors such as panic or aggression, that can very rapidly change based on unexpected new elements introduced into the environment. We present preliminary research specifically oriented towards the simulation of large crowds for emergency response and rescue planning situations. Our approach uses a highly scalable architecture integrated with an efficient rendering architecture and an immersive visualization environment for interaction. In this environment, users can specify complex scenarios, "plug-in" crowd behavior algorithms, and interactively steer the simulation to analyze and evaluate multiple "what if" situations.

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