Cellular Automata Model for Helping Behavior in Pedestrian Evacuation Based on Fuzzy Theory

Abstract

Evacuation accidents have been frequent in recent years, and during evacuation we know that people do not always act selfishly. This study aims to investigate the effect of helping behavior on evacuation efficiency. Through the fuzzy logic reasoning method combined with the cellular automata (CA) model, we investigated the role of helping behavior on evacuation efficiency in different contexts and came up with the following results. Firstly, we found that helping behavior has a positive effect on evacuation efficiency to some extent and can significantly reduce evacuation time. At an average personnel density of approximately 1.38 persons per square meter, individuals involved in helping behavior are able to provide assistance and speed up the evacuation process. However, when the personnel density is too high, helping behavior may instead reduce evacuation efficiency. This may be attributable to the blockage of exits in high-density situations, resulting in a weakening of the synergistic effect of helping behavior. The findings elucidate the dual-edged nature of helping behavior in evacuations and emphasize the importance of strategic planning and crowd management to harness its potential benefits effectively.