High-density Real-time Virtual Crowds via Unilaterally Incompressible Fluid Simulation

Human crowds experience limited individual freedom of motion and tend to exhibit aggregate behavior at high densities. This observation can be exploited in simulations by representing virtual crowds as both distinct agents and continua. We introduce a global planning algorithm suitable for navigating large virtual crowds of agents. These crowds are in turn modeled as unilaterally incompressible fluids to effectively simulate large-scale behavior. The algorithm is ultimately tested on certain specific scenarios with the intention of detecting common emergent behaviors, to finally draw conclusions on its ability to simulate real-life situations.