Robot-Guided Crowd Evacuation in a Railway Hub Station in Case of Emergencies

The rapid and orderly evacuation of passengers at the railway hub station in case of emergencies is an important issue for railway safety and efficiency. In this paper, a robot-guided passenger evacuation method is proposed to help passengers search evacuation paths and avoid potential risks. The number and initial positions of robots are determined by using a k-means clustering approach. The exit assignment and evacuation paths of robots are calculated by using a hybrid bi-level optimization approach taking into account the cooperative mechanism between robots. Then, a robot-guided crowd evacuation dynamical model is built based on a modified social force model, in which a navigation force is introduced to influence the speed and direction of evacuees. A case study of a typical railway hub station is used to demonstrate the effectiveness of the proposed approach. The scenarios of the mall and platform are designed to verify the evacuation efficiency under different robot distribution schemes. The experimental results prove that setting up robots can effectively reduce evacuation time, and the utilization of exits is more balanced. The proposed optimal scheme shows the best performance in evacuation efficiency, including evacuation time and exit utilization rate, compared to the uniform distribution scheme and no robot scheme.