Simulation of emergency evacuation in subway station

Author(s):  
Yan Liu ◽  
Tong Wang ◽  
Zongzhi Wu
2021 ◽  
Vol 13 (22) ◽  
pp. 12540
Author(s):  
Heng Wang ◽  
Zehao Jiang ◽  
Tiandong Xu ◽  
Feng Li

Subway station emergencies are gradually increasing in China. The aim of this research is to study the effects of “Dist”, “Pedestrian flow” and “Crowd density” on the heterogeneity of passengers’ decision-making preference and explore the relationship between heterogeneity and personality. Firstly, a questionnaire of 20 emergency evacuation scenarios, that includes the Eysenck Personality Questionnaire, is designed. Secondly, the heterogeneity of passengers’ decision preference is quantified by the random parameter logit model. Finally, personality traits and influencing factors are used as abscissa and ordinate respectively, to study the relationship between personality traits and preference heterogeneity. The results show that the coefficients of “Dist”, “Pedestrian flow” and “Crowd density” are –0.101, 0.236 and –0.442 respectively, which are statistically significant. The proportion of extroverted passengers of the exit is 9% higher than that of introverted passengers when “Pedestrian flow” of the exit is greater than the average value, while the proportion of introverted passengers is 7% higher than that of extroverted passengers when “Crowd density” is smaller than the average value. The conclusion is that the three influence factors are random variables, and “Dist” shows the lowest level of heterogeneity. Extroverted passengers are more likely to follow a large crowd for evacuation, but introverted passengers are more likely to avoid crowded exits.


2021 ◽  
Author(s):  
Xiao-Xia Yang ◽  
Hai-Long Jiang ◽  
Yuan-Lei Kang ◽  
Yi Yang ◽  
Yong-Xing Li ◽  
...  

Abstract Under the background of Covid-19 sweeping the world, safe and reasonable passenger flow management strategy in subway stations is an effective means to prevent the spread of virus. Based on the social force model and the minimum cost model, the movement and path selection behavior of passengers in the subway station are modeled, and a strategy for passenger flow management to maintain a safe social distance is put forward. Take Qingdao Jinggangshan Road subway station of China as the simulation scene, the validity of the simulation model is verified by comparing the measured value and simulation value of the time required for passengers from getting off the train to the ticket gate. Simulation results indicate that controlling the time interval between incoming passengers at the entrance can effectively control the social distance between passengers and reduce the risk of epidemic infection. By comparing the evacuation process of passengers under different initial densities, it is found that the greater the initial density of passengers, the longer the passengers are at risk social distance. In the process of passenger emergency evacuation, the stairs/escalators and ticket gates are bottleneck areas with high concentration of passenger density, which should be strictly disinfected many times on the basis of strictly checking the health code of incoming passengers and controlling the arrival time interval. The simulation results of this paper verify the harmfulness of passenger emergency evacuation without protective measures, and provide theoretical support for the operation and management of subway station under the epidemic situation.


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