This projects develops a psychological model for simulating pedestrian behaviors in a crowded space. Our decision-making scheme controls plausible avoidance behavior depending on the positional relations among surrounding persons, on the basis of a two-stage personal space and a virtual memory structure as proposed in social psychology. Our system determines pedestrian walking speed with the crowd density to imitate the measured data in urban engineering, and automatically generates plausible motions of the individual pedestrian by composing a locomotion graph with motion capture data. Our approach based on psychology and a variety of actual measurements ensures the accuracy of simulation at both the micro and macro levels.
Demonstration for CASA2005
QuickTime: 14 MB, No Audio