Emergence of diverse collective behaviors from local topological perception

We present a dynamical model for generic crowds in 2D in which individual agents are aware of their local environment -- i.e., neighboring agents and domain boundary features -- and may seek static target locations. Our model incorporates features common to many other "active matter" models like collision avoidance, alignment among agents, and homing toward targets. However, it is novel in key respects: the model combines topological and metrical features in a natural manner based upon the local environment of the agent's Voronoi diagram. With only two parameters, it is shown to capture a wide range of collective behaviors.