Improving Flexibility of Agent’s Path Selection in Cellular Pedestrian Flow Model

Abstract

Motivated by the results of an exit selection experiment, this paper presents an agent-based cellular automaton with a new path selection approach. In our model, an agent first selects a target cell within a look-ahead distance by avoiding conflictwith other agents and minimizing the distance to destination. Then, the agent moves to the neighbor cell which minimizes the distance to the selected target and the repulsion induced by other agents. Simulation of the experiment with our new model gives more realistic results than with a simple model taking account of only local information. Furthermore, our model successfully simulates self-organized phenomena such as lane formation.