Crowd Simulation with Deliberative-Reactive Agents

Abstract

Crowd dynamics are emergent processes caused by local pedestrian interactions. In this work, we describe a decentralized crowd simulation model based on deliberative-reactive agents. The model simulates fire evacuation scenarios and includes specific behaviors such as collisions, panic, bottleneck and cluster formation. The environment interactions are passive (fire alarms) or active (adaptive guidance indicators). Results show that the model is able to generate higher level dynamics through emergence. An analysis based on psychological reaction time shows that the crowd behaves like an organic whole, aligning with observations of real-world human crowds. This paper is a summary of "Predictive Agent-Based Crowd Model Design Using Decentralized Control Systems" published in IEEE Systems Journal (2022).