Simulation of subway passenger flow during station evacuation based on K-shortest path planning and an improved social force model

Urban rail transit stations experience a high passenger flow density, resulting in complex passenger movement within the station premises. Efficient and prompt passenger evacuation can be achieved by strategically planning evacuation routes in alignment with a station’s environmental characteristics and passenger flow patterns. To address the problem of adaptive social force models not being able to plan evacuation routes for pedestrians in real-time based on station exit opening and closing information, a method for the simulation of subway station passenger flow evacuation based on the social force model and improved K-shortest path planning is proposed. Through enhancements to the conventional Yen algorithm, this method can efficiently determine K-shortest paths that guide passengers to multiple evacuation exits, thus providing vital path information during evacuation procedures. A simulation experiment simulating crowd evacuation was devised within a simplified scenario in order to assess the effectiveness of our approach. The outcomes of this experiment clearly demonstrate the superior evacuation performance achieved when combining the adaptive social force model with improved K-shortest path planning. Moreover, the proposed method has been applied to a passenger flow evacuation simulation experiment within a subway station setting. These experimental results conclusively affirm the feasibility and practical applicability of our simulation technique for conducting passenger flow evacuation simulations within subway stations.