Cellular automata model of emergent collective bi-directional pedestrian dynamics

This paper describes the application of an Artificial Life cellular automata (CA) microsimulation to model the emergent collective behavior of bi-directional pedestrian flows. Since pedestrian flow is inherently complex, even more so than vehicular flow, previous CA models developed for vehicle flow are not directly applicable. It is shown that a relatively small rule set is capable of effectively capturing the collective behaviors of pedestrians who are autonomous at the micro-level. The model provides for simulating three modes of bi-directional pedestrian flow: (a) flows in directionally separated lanes, (b) interspersed flow, and (c) dynamic multi-lane flow. The emergent behavior that arises from the model is consistent with well-established fundamental properties of pedestrian flows.