Collective behavior of human crowds

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Whether walking down a busy sidewalk or a crowded mall, we effortlessly coordinate our movements with other pedestrians. Sometimes we weave through the crowd, dodging our neighbors; at other times we merge into a coherent "swarm," much like a flock of birds or a school of fish, and may spontaneously form lanes in opposite directions, similar to columns of ants. Where do these basic traffic patterns come from? It is generally believed that collective behavior in humans and animals emerges from local interactions between neighbors, rather than from a central plan or leader, but the actual mechanisms are unclear. By studying the perceptual-motor "rules" that govern interactions between neighbors, the investigator aims to determine whether crowd behavior can be explained by local interactions. The resulting model will enable realistic simulation of pedestrian traffic flow. Its potential broader impacts are to architectural design, evacuation planning, computer animation, and the development of assistive technology for blind and low-vision users. There are many models of collective swarm behavior in fields ranging from physics and computer science to animal behavior and urban planning, yet they are based on little experimental data. The key weakness of existing theories is a dearth of knowledge about the visual coupling between neighbors -- the perceptual-motor rules, forces, or control laws that govern pedestrian interactions. The goal of this project is to develop a cognitively grounded pedestrian model and test the hypothesis that global crowd behavior emerges from these local interactions. An innovative research program combines (a) a local-to-global approach, in which the visual coupling is mapped out in experiments with virtual crowds, and used to predict crowd behavior in multi-agent simulations, and (b) a global-to-local approach, in which experiments on real crowds are analyzed and used to test the model. The aim is to account for pedestrian and crowd dynamics and elucidate the relation between "micro" and "macro" levels of collective behavior.