Extended Floor Field Cellular Automata Model for Pedestrian Emergency Evacuation Considering Panic Emotion

Abstract

Panic emotion appears frequently in an emergency evacuation, affecting evacuation efficiency and pedestrian safety. Individual diversity in emotion propagation causes pedestrians to behave differently. To better describe the emotion propagation in the movement of pedestrians, we analyze the characteristics of the emotions of different pedestrians in emergencies. Considering pedestrian heterogeneity, we divide pedestrians into three types (conservative, moderate, and radical) according to the strength of the expression of individual emotions. Based on an analysis of the characteristics of the three types of pedestrian, an improved susceptible-infected-recovered (SIR) model is built to describe the pedestrian emotion propagation process. In addition, a conflict avoidance method that considers pedestrian speed is proposed to demonstrate pedestrian motion more realistically. Based on this foundation, a cellular automata (CA) model that integrates emotion propagation and conflict avoidance techniques is employed to replicate the process of pedestrian emergency evacuation. The simulation results suggest that a higher proportion of pedestrians with initial panic emotions and a radical behavior type leads to a prolonged evacuation time. Many pedestrians in emergency evacuations gather at the exit in a short time (approximately 37 time steps), the density then reaches a high-level (approximately 5.5 pedestrians/m2) for a period of time, and the duration increases with the increase in the number of pedestrians. Methods for guiding pedestrians to evacuate in a rational manner are worthy of promotion and research.