MOTOR SCHEMA-BASED CELLULAR AUTOMATON MODEL FOR PEDESTRIAN DYNAMICS

Abstract

A new cellular automaton model for pedestrian dynamics based on motor schema is presented. Each pedestrian is treated as an intelligent mobile robot, and motor schemas including move-to-goal, avoid-away and avoid-around drive pedestrians to interact with their environment. We investigate the phenomenon of many pedestrians with different move velocities escaping from a room. The results show that the pedestrian with high velocity have predominance in competitive evacuation, if we only consider repulsion from or avoiding around other pedestrians, and interaction with each other leads to disordered evacuation, i.e., decreased evacuation efficiency. Extensions of the model using learning algorithms for controlling pedestrians, i.e., reinforcement learning, neural network and genetic algorithms, etc. are noted.