An emergency exits choice preference model based on characteristics of individual diversity

Previously compute models usually applied the assumption that people would adopt the shortest route to escape, or be given fixed destination. But the diversity of characteristics mean everyone has an individual determination based on optimal utility including distance, crowding level, and personalized cognition. We focused on the correlation between individual feature and their initial exits strategy in crowded places. By carrying out a questionnaire survey about individual characteristics, spatial cognition, and personalized decision in a market, we found that each pedestrian held different preferences and probabilities of choosing a particular exit for evacuation due to diversity of social background. An emergency exits choice preference model was proposed to analyze escape behavior and to determine the initial preference. The model could balance the influence of differentiated cognition of various pedestrians against the practical evacuating state and surroundings. And also, it could predict the destinations choosing probability in emergency. The result showed the evacuation duration, maximum density, and highest density were more optimal. Applying this model, the pedestrians’ averaged density of exits decreased obviously. Stampede risk was significantly reduced. We expected to make a step that the pedestrian behavior simulation will advance on integrating the human social behavior from theoretical precision.