Bidirectional Evacuation in Subway Fires Considering the Number of Retrograders and Proactive Avoidance Behavior Based on Experiments and Simulations

Abstract

Subway fires often cause significant casualties and property losses. There are some special bidirectional coupling scenarios during subway fires, such as firefighters moving against the evacuation flow to extinguish fires, emergency managers going to the fire scene to respond to emergencies, or other similar scenarios. How to evacuate passengers quickly and enable responders to enter the fire scene has become a big challenge for subway fire evacuation and response. The core goal is to reduce the degree of mutual interaction between these people moving in opposite directions. In this study, the impact of counterflow individuals and proactive avoidance behavior on evacuation processes was investigated through experiments and simulations. The Fire Dynamic Simulator was used to simulate the development of a fire scenario to determine the available safe egress time. Micro-evacuation experiments were conducted to obtain actual evacuation parameters, such as the speeds of different objects. With these parameters as input, a macro subway fire scenario was built to simulate the bidirectional evacuation process. Consistent conclusions were obtained from the experiments and evacuation simulations. The results indicate that the overall evacuation time increases with the number of retrograders. Proactive avoidance behavior can effectively reduce the travel time of counterflow individuals, but it causes slight delays for forward-moving evacuees. An optimization strategy was implemented through conductor guidance. All passengers can successfully evacuate under the optimization strategy, with a 25.3% improvement in overall evacuation time. This research provides some insights into the coordinated evacuation and emergency response during subway fires or similar scenarios.

References

[] Abir, I.M., A. Mohd Ibrahim, S.F. Toha, and A.A. Shafie. 2022. A review on the hospital evacuation simulation models. International Journal of Disaster Risk Reduction 77: Article 103083.

[] Cai, Z., R. Zhou, Y. Cui, Y. Wang, and J. Jiang. 2022. Influencing factors for exit selection in subway station evacuation. Tunnelling and Underground Space Technology 125: Article 104498.

[] Chen, J., C. Liu, Y. Meng, and M. Zhong. 2021. Multi-dimensional evacuation risk evaluation in standard subway station. Safety Science 142: Article 105392.

[] Chen, J., Z. Long, L. Wang, B. Xu, Q. Bai, Y. Zhang, C. Liu, and M. Zhong. 2022. Fire evacuation strategy analysis in long metro tunnels. Safety Science 147: Article 105603.

[] Chen, Y., C. Wang, J.B. Hui Yap, H. Li, and S. Zhang. 2020. Emergency evacuation simulation at starting connection of cross-sea bridge: case study on Haicang Avenue Subway Station in Xiamen Rail Transit Line. Journal of Building Engineering 29: Article 101163.

[] Cheng, C.H., C.L. Chow, and W.K. Chow. 2021. A simulation study of tenability for passengers in a railway tunnel with arson fire. Tunnelling and Underground Space Technology 108: Article 103679.

[] Fu, L., Y. Liu, H. Qin, Q. Shi, Y. Zhang, Y. Shi, and J.T.Y. Lo. 2022. An experimental study on bidirectional pedestrian flow involving individuals with simulated disabilities in a corridor. Safety Science 150: Article 105723.

[] Gao, J., J. Gong, J. He, D. Zhang, G. Qiu, and J. Zhang. 2020. Experimental study on pedestrians’ uni- and bi-directional movement on staircases under emergency conditions. Journal of Statistical Mechanics: Theory and Experiment 2020: Article 103401.

[] GaoR, LiA, HaoX, LeiW, DengB. Prediction of the spread of smoke in a huge transit terminal subway station under six different fire scenarios. Tunnelling and Underground Space Technology, 2012, 31: 128-138

[] GaoR, LiA, ZhangY, LuoN. How domes improve fire safety in subway stations. Safety Science, 2015, 80: 94-104

[] GuoX, PanX, WangZ, YangJ, HuaM, JiangJ. Numerical simulation of fire smoke in extra-long river-crossing subway tunnels. Tunnelling and Underground Space Technology, 2018, 82: 82-98

[] Han, Y., H. Liu, and L. Li. 2023. An evacuation guidance model for pedestrians with limited vision. Transportmetrica A Transport Science 19(1): Article 1977867.

[] HuangY, CaoD. Decision response of subway evacuation signs based on brain component features. Neural Computing and Applications, 2021, 34(9): 1-15

[] Huang, Z., S. Cao, Z. Fang, R. Ye, Z. Wang, and X. Li. 2021. Effect of voice alarms on temporal characteristics of the evacuation process inside metro train carriages: An experiment study. Safety Science 142: Article 105403.

[] Jin, C.-J., K.-D. Shi, R. Jiang, D. Li, and S. Fang. 2023. Simulation of bi-directional pedestrian flow under high densities using a modified social force model. Chaos, Solitons & Fractals 172: Article 113559.

[] KongJ, YouW, XuZ, LiuH, LiH. A numerical study on smoke behaviors in inclined tunnel fires under natural ventilation. Journal of Safety Science and Resilience, 2022, 3(2): 169-178

[] Lan, B., Y.-R. Li, P.-C. Li, and H.-F. Gong. 2022. Numerical simulation of the chimney effect on smoke spread behavior in subway station fires. Case Studies in Thermal Engineering 39: Article 102446.

[] Lin, Y., and B. Zhou. 2024. A numerical simulation-based solution for enhancing the safety evacuation of the high-rise complex in geriatric hospital. International Journal of Disaster Risk Reduction 107: Article 104487.

[] Liu, D.D. 2010. Survey and analysis of pedestrian characteristics in subway of Beijing. Building Science 26(3): 70–74; 83.

[] LiuS, LiuJZ, WeiW. Simulation of crowd evacuation behaviour in outdoor public places – A model based on Shanghai stampede. International Journal of Simulation Modelling, 2019, 18(1): 86-99

[] Long, Z., J. Chen, P. Qiu, and M. Zhong. 2022. Study on the smoke layer height in subway platform fire under natural ventilation. Journal of Building Engineering 56: Article 104758.

[] Long, Z., M. Zhong, J. Chen, and H. Cheng. 2023. Study on emergency ventilation strategies for various fire scenarios in a double-island subway station. Journal of Wind Engineering and Industrial Aerodynamics 235: Article 105364.

[] LuoN, LiA, GaoR, TianZ, HuZ. Smoke confinement utilizing the USME ventilation mode for subway station fire. Safety Science, 2014, 70: 202-210

[] MengN, HuL, WuL, YangL, ZhuS, ChenL, TangW. Numerical study on the optimization of smoke ventilation mode at the conjunction area between tunnel track and platform in emergency of a train fire at subway station. Tunnelling and Underground Space Technology, 2014, 40: 151-159

[] MengQ, ZhouM, LiuJ, DongH. Pedestrian evacuation with herding behavior in the view-limited condition. IEEE Transactions on Computational Social Systems, 2019, 6(3): 567-575

[] PanZ, WeiQ, WangH. Agent-based simulation of hindering effect of small group behavior on elevated interval evacuation time along urban rail transit. Travel Behaviour and Society, 2021, 22: 262-273

[] Qin, J., C. Liu, and Q. Huang. 2020. Simulation on fire emergency evacuation in special subway station based on Pathfinder. Case Studies in Thermal Engineering 21: Article 100677.

[] Ren, J., Z. Mao, D. Zhang, M. Gong, and S. Zuo. 2022. Experimental study of crowd evacuation dynamics considering small group behavioral patterns. International Journal of Disaster Risk Reduction 80: Article 103228.

[] Shan, S., X. Guo, Z. Wei, W. Sun, H. Zheng, H. Pan, and J. Lin. 2023. Simulation analysis of evacuation processes in a subway station based on multi-disaster coupling scenarios. International Journal of Disaster Risk Reduction 96: Article 103998.

[] ShiwakotiN, GongY, ShiX, YeZ. Examining influence of merging architectural features on pedestrian crowd movement. Safety Science, 2015, 75: 15-22

[] SpyrouKJ, ThemelisN, NikolaouN. SoaresG, PeñaL. Towards risk-based fire safety assessment of passenger ships. Developments in maritime transportation and exploitation of sea resources, 2013 London Taylor & Francis Group 797-804

[] Su, Z., and X. Li. 2022. Analysis of energy-saving for ventilation and air-conditioning system of subway stations with platform screen doors. Journal of Building Engineering 59: Article 105064.

[] Su, L.-C., X. Wu, X. Zhang, and X. Huang. 2021. Smart performance-based design for building fire safety: Prediction of smoke motion via AI. Journal of Building Engineering 43: Article 102529.

[] SunY. Simulations of bi-direction pedestrian flow using kinetic Monte Carlo methods. Physica A: Statistical Mechanics and its Applications, 2019, 524: 519-531

[] Tan, T., L. Yu, L. Ding, Z. Gao, and J. Ji. 2021. Numerical investigation on the effect of ambient pressure on mechanical smoke extraction efficiency in tunnel fires. Fire Safety Journal 120: Article 103136.

[] TsukaharaM, KoshibaY, OhtaniH. Effectiveness of downward evacuation in a large-scale subway fire using fire dynamics simulator. Tunnelling and Underground Space Technology, 2011, 26(4): 573-581

[] von KrüchtenC, SchadschneiderA. Empirical study on social groups in pedestrian evacuation dynamics. Physica A: Statistical Mechanics and its Applications, 2017, 475: 129-141

[] Wang, J., J. Li, J. Li, J. Feng, S. Xu, J. Liu, and Y. Wang. 2022. Performance optimization of the obstacle to corner bottleneck under emergency evacuation. Journal of Building Engineering 45: Article 103658.

[] Wang, K., W. Yuan, W. Liang, and Y. Yao. 2023. An optimal guidance strategy for fire evacuations: a hybrid modeling approach. Journal of Building Engineering 73: Article 106796.

[] WengM-C, LuX-L, LiuF, ShiX-P, YuL-X. Prediction of backlayering length and critical velocity in metro tunnel fires. Tunnelling and Underground Space Technology, 2015, 47: 64-72

[] Wu, K., X. Chen, J. Li, L. Zhang, K. Zhu, Y. Hong, and T. Zhang. 2023. Flame behavior and fire-induced flow field characteristic in building corridor fire with longitudinal partition. Journal of Building Engineering 76: Article 107358.

[] Xie, W., E.W.M. Lee, Y. Cheng, M. Shi, R. Cao, and Y. Zhang. 2020. Evacuation performance of individuals and social groups under different visibility conditions: Experiments and surveys. International Journal of Disaster Risk Reduction 47: Article 101527.

[] XuH-H, GuoR-Y. Simulation of bi-directional pedestrian flow by using a cell transmission model. Simulation Modelling Practice and Theory, 2018, 87: 1-14

[] Xu, L., K. Huang, J. Liu, D. Li, and Y.F. Chen. 2022. Intelligent planning of fire evacuation routes using an improved ant colony optimization algorithm. Journal of Building Engineering 61: Article 105208.

[] Xue, S., F. Claudio, X. Shi, and T. Li. 2020. Revealing the hidden rules of bidirectional pedestrian flow based on an improved floor field cellular automata model. Simulation Modelling Practice and Theory 100: Article 102044.

[] Yan, Z., Y. Wang, and L. Chao. 2023. Simulation study on fire and evacuation of super high-rise commercial building. Case Studies in Thermal Engineering 52: Article 103519.

[] YangX, BanX, MitchellJ. Modeling multimodal transportation network emergency evacuation considering evacuees’ cooperative behavior. Transportation Research Procedia, 2017, 23: 1038-1058

[] Yang, X.X., H.I. Dong, X.M. Yao, and X.B. Sun. 2016. Pedestrian evacuation at the subway station under fire. Chinese Physics B 25(4): Article 048902.

[] YangP, LiC, ChenD. Fire emergency evacuation simulation based on integrated fire-evacuation model with discrete design method. Advances in Engineering Software, 2013, 65: 101-111

[] YangX, ZhangR, LiY, PanF. Passenger evacuation path planning in subway station under multiple fires based on multiobjective robust optimization. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(11): 21915-21931

[] Yu, H., Y. Wang, P. Qiu, and J. Chen. 2019. Analysis of natural and man-made accidents happened in subway stations and trains: based on statistics of accident cases. MATEC Web of Conferences 272: Article 01031.

[] YueH, GuanH, ZhangJ, ShaoC. Study on bi-direction pedestrian flow using cellular automata simulation. Physica A: Statistical Mechanics and its Applications, 2010, 389(3): 527-539

[] ZhangN, LiangY, ZhouCF, NiuMM, WanF. Study on fire smoke distribution and safety evacuation of subway station based on BIM. Applied Sciences, 2022, 12(24): 12808-12808

[] Zhang, Q., J. Qu, and Y. Han. 2023a. Pedestrian small group behaviour and evacuation dynamics on metro station platform. Journal of Rail Transport Planning & Management 26: Article 100387.

[] ZhangL, WuX, LiuM, LiuW, AshuriB. Discovering worst fire scenarios in subway stations: a simulation approach. Automation in Construction, 2019, 99: 183-196

[] Zhang, Y., X. Zhang, and X. Huang. 2023b. Design a safe firefighting time (SFT) for major fire disaster emergency response. International Journal of Disaster Risk Reduction 88: Article 103606.

[] Zhuang, Y., Z. Liu, A. Schadschneider, L. Yang, and J. Huang. 2021. Exploring the behavior of self-organized queuing for pedestrian flow through a non-service bottleneck. Physica A: Statistical Mechanics and its Applications 562: Article 125186.