A Fuzzy-Theory-Based Cellular Automata Model for Pedestrian Evacuation From a Multiple-Exit Room

Abstract

The exit selection behavior of pedestrians plays an important part in the process of evacuation. This paper proposes a cellular automata model based on fuzzy logic method for simulating the evacuation of pedestrians from a multiple-exit room. When pedestrians select the exit, the distance and density are adopted as two important input variables in the fuzzy logic method, and the probability of selecting each exit is defined as the output variable of fuzzy logic method. The output variable of fuzzy logic, exit width and herding behavior are combined to determine the target exit. The competitiveness of each pedestrian is calculated by logit model to solve the position conflicts among pedestrians. The validation of the model is demonstrated by comparing the simulation data with the real data. The effects of attributes of pedestrians, exits and obstacles on evacuation are studied in simulations. Results show that large public facilities should control the inflows of pedestrians, and the reasonable increase of the exit quantity and exit width are effective for improving the evacuation efficiency. In the design of buildings, obstacles need to be designed reasonably, which should not be too large or too small. At the same time, obstacles should be kept at a certain distance from the exit, so as to ease the exit congestion and improve the evacuation efficiency. This paper takes the advantages of fuzzy logic method to solve the exit selection problem, which can effectively integrate the robustness with physiological-based “perception-action” behavior, the experience knowledge of pedestrians and the perception information of the surrounding environment into the decision-making process.

Keywords

• Cellular automata model
• exit selection
• fuzzy logic method
• logit model
• pedestrian evacuation