Modeling Movement Direction Choice and Collision Avoidance in Agent-Based Model for Pedestrian Flow

Abstract

AbstractAgent-based microscopic pedestrian-flow simulation models are promising tools for designers or engineers to evaluate the level of safety or comfort of crowded pedestrian traffic facilities. Existing models tend to simulate movement direction choice behaviors of a virtual agent based on a joint effect of several physical, psychological, and sociological factors dominating the real-world pedestrian walking behaviors. Challenging questions remain for this type of model, including how to control and balance the influences among these behavioral factors and how to naturally avoid collisions without losing the effect of the behavior factors considered. This article presents an improved utility-maximization approach to determine the movement direction of individuals in an agent-based pedestrian-flow simulation model. A new utility function is proposed. An explicit collision detection and avoidance technique is used as a supplementary rule together with the utility maximization method to improve the colli...