Sensor-Based Pedestrian Movement Simulation and Evacuation Strategy in Emergencies

Research on pedestrian movement is of great significance for public safety management and the formulation of safe evacuation strategies. The compatibility effect of approaching the positive and avoiding the negative is a common phenomenon in pedestrian movements, there is a compatibility relationship between emotional stimuli and approach avoidance behavior, individuals are faster in avoiding than in approaching negative stimuli, they are faster in approaching than in avoiding positive stimuli, and emotional difference is an important reason for this phenomenon. However, current pedestrian movement models cannot simulate the movement phenomenon caused by emotional differences, the application of sensors mainly focuses on real-time navigation and scene monitoring, and research on sensor-based pedestrian movement simulation is lacking. These reduce the effect of pedestrian movement simulation and the crowd evacuation efficiency. For this purpose, a sensor-based pedestrian movement simulation and evacuation method is proposed in this article. First, image sensors are used to collect multiple media data (images and videos), and an emotional perception model is proposed to associate pedestrians’ emotional states with their movement characteristics. Then, an emotional difference-based pedestrian movement model (ED-PMM) is constructed to describe the compatibility effect of approaching the positive and avoiding the negative in pedestrian movements. Finally, based on wireless sensors, a personalized path planning method considering the emotional differences of pedestrians is designed to guide pedestrians to evacuate. The experiment results show that the ED-PMM can improve the simulation effect of pedestrian movement and the evacuation strategy can improve the evacuation efficiency.