In the emergency evacuation of pedestrians in subway stations, most people do not know the correct evacuation routes and methods, and tend to follow others blindly, resulting in herding behavior. To study the process of pedestrian evacuation with herding behavior in subway stations, a cellular automata pedestrian evacuation model is established to simulate the pedestrian evacuation with herding behavior in subway stations, and the effects of the weight coefficients of the parameters in the model on the overall evacuation time and the distribution of people’s positions are investigated to quantify the effects of herding on the efficiency of the pedestrian evacuation and the movement behavior. The simulation results show that moderate (kC < 40) crowd behavior can play a beneficial role in reducing reaction time and guiding the direction of evacuation; on the contrary, excessive crowd behavior (kC > 40) will lead to an increase in evacuation time and a decrease in evacuation efficiency. The conclusions presented in this paper can help to improve the efficiency of pedestrian evacuation in emergencies and provide a theoretical basis and practical guidance for the management of safety evacuation in subway stations.
Dong L, Yuan W, Deng Y, 2023, A Study of Evacuation Model based on Personnel Vision Change. Journal of Intelligent & Fuzzy Systems, 44(4): 6231–6247.
Pereira LA, Burgarelli D, Duczmal LH, et al., 2017, Emergency Evacuation Models based on Cellular Automata with Route Changes and Group Fields. Physica A: Statistical Mechanics and its Applications, 2017(473): 97–110.
Yu T, Yang HD, 2023, Simulation of Running Crowd Dynamics: Potential-based Cellular Automata Model. IEEE Access, 2023(99):1.
Chen Y, Wang C, Li H, et al., 2020, Cellular Automaton Model for Social Forces Interaction in Building Evacuation for Sustainable Society. Sustainable Cities and Society, 2020(53): 101913.
Guo K, Zhang L, Wu M, 2023, Simulation-based Multi-objective Optimization Towards Proactive Evacuation Planning at Metro Stations. Engineering Applications of Artificial Intelligence, 2023(120): 105858.
Yuan XT, Tang TQ, Chen L, 2023, A Fine Grid Cellular Automaton Model for Pedestrian Evacuation Considering the Effect of an Obstacle. Simulation, 99(9): 957–968.
Du E, Wu F, Jiang H, et al., 2022, Development of an Integrated Socio-hydrological Modeling Framework for Assessing the Impacts of Shelter Location Arrangement and Human Behaviors on Flood Evacuation Processes. Hydrology and Earth System Sciences Discussions, 27(7): 1–49.
Lumbroso D, Davison M, Wetton M, 2023, Development of an Agent-based Model to Improve Emergency Planning for Floods and Dam Failures. Journal of Hydroinformatics, 25(5): 1610–1628.
Quagliarini E, Bernardini G, Romano G, et al., 2022, Simplified Flood Evacuation Simulation in Outdoor Built Environments: Preliminary Comparison between Setup-based Generic Software and Custom Simulator. Sustainable Cities and Society, 2022(81): 103848.
Wang K, Yuan W, Yao Y, 2023, Path Optimization for Mass Emergency Evacuation based on an Integrated Model. Journal of Building Engineering, 2023(68): 106112.
Alonso VS, Mazzoleni M, Bhamidipati S, et al., 2020, Unravelling the Influence of Human Behaviour on Reducing Casualties during Flood Evacuation. Hydrological Sciences Journal, 65(14): 2359–2375.
Masson-Delmotte V, Zhai P, Pirani A, et al., 2021, Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Climate Change 2021: The Physical Science Basis.