Journal Article•
Virtual assessment model on emergency evacuation capacity of Beijing subway based on BP neural network algorithm
TL;DR: By applying the BP neural network algorithm and MATLAB software, the index system of emergency evacuation was established by selecting the relative factors that might influence the evacuation capacity of subway station as assessment index.
Abstract: The emergency evacuation capacity of subway station is a quite important part of safety operation design of subway,with great significance to maintain social stability and ensure people securityIn this paper,by applying the BP neural network algorithm and MATLAB software,the index system of emergency evacuation was established by selecting the relative factors that might influence the evacuation capacity of subway station as assessment indexTaking the subway stations around the North 3rd Ring area in Beijing as main objects,the virtual assessment on emergency evacuation capacity of subway station in Beijing was conductedSome suggestions that can be referenced were put forward,such as increase the quantity of evacuation routes,stairs and exits,so as to improve the emergency evacuation capacity of subway station
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TL;DR: The design of an optimal route for emergency evacuation is the main theme of most studies focusing on environmental factors, and human-related factors focusing on injury prevention are also crucial.
Abstract: Background: Due to the extensive use of subway transportation in high- and middle-income countries, the safety of passengers has become one of the important challenges in emergency management of subway station. Therefore, the present systematic review aimed to identify environmental and organizational management factors that affect the safe emergency evacuation in subway stations. Materials and Methods: In this systematic literature review, PubMed, Scopus, Web of Science, ProQuest, Google Scholar, Iran Medex, Magiran, and Scientific Information Database from 1990 to 2019 were searched to identify effective emergency management factors in safe emergency evacuation of the subways. A thematic content analysis was employed for data analysis. Results: Of 763 publications retrieved from the searches, 149 studies were included for data analysis. According to the findings, effective environmental and organizational management factors in safe emergency evacuation were discussed in eight subcategories, including infrastructure properties, evacuation-assisting resources, prevention of injuries and mitigation, preparedness for emergency evacuation, emergency response and reconstruction, and maintenance of evacuation facilities. Conclusion: The design of an optimal route for emergency evacuation is the main theme of most studies focusing on environmental factors. While a system approach for designer is needed for effective subway emergency evacuation, human-related factors focusing on injury prevention are also crucial.
31 citations
01 Aug 2016
TL;DR: Assessment results show that the overall emergency evacuation ability of the Beijing metro lines subway example can only catch the average level.
Abstract: Subway has become one of main means of transportation all over the world. How to deal with sudden subway accident is the serious problem the whole world should face to. In view of subway security issues, choosing one of Beijing metro lines as the research example, building a warning index system include of 14 indexes such as fire warning ability, power system, etc. and using the neural network model to simulate and assess the emergency evacuation capacity of the subway example. The assessment results show that the overall emergency evacuation ability can only catch the average level. The subway example have the characters of built early time, relatively old technical level, long operation time, a large number of exchange station along the central and large traffic lines, large amount passengers all the year round. Then it is put forward to increase the subway station evacuation ability, especially transfer subway lines as well as the station with the weak ability of evacuation exit, which provides a reference for improving the capacity of the subway emergency evacuation.
9 citations
Cites background from "Virtual assessment model on emergen..."
...Correspondingly, it is conducive to improve the emergency evacuation ability of subway operation which the indicator of the best value in each station is set to 1 and the worst value is 0 [15]; a=max (p'); for i=1:14 for j=1:18 ptest ( i, j )=p(i,j)/a(i); end end (2) training sample setting....
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...For example, value of fire early warning capability is a logical type, which namely means the subway fire early warning ability value is 1, otherwise the value of 0 [15];Exit preparation is numeric, it indicates the number of setting exit in the subway station....
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TL;DR: Zhang et al. as discussed by the authors proposed a method based on improved YOLOv5s target detection and Anylogic emergency evacuation simulation to improve the efficiency of emergency evacuation of field stations and further protect people's lives.
Abstract: With the development of the social economy and the continuous growth of the population, emergencies within field stations are becoming more frequent. To improve the efficiency of emergency evacuation of field stations and further protect people’s lives, this paper proposes a method based on improved YOLOv5s target detection and Anylogic emergency evacuation simulation. This method applies the YOLOv5s target detection network to the emergency evacuation problem for the first time, using the stronger detection capability of YOLOv5s to solve the problem of unstable data collection under unexpected conditions. This paper first uses YOLOv5s, which incorporates the SE attention mechanism, to detect pedestrians inside the site. Considering the height of the camera and the inability to capture the whole body of the pedestrian when the site is crowded, this paper adopts the detection of the pedestrian’s head to determine the specific location of the pedestrian inside the site. To ensure that the evacuation task is completed in the shortest possible time, Anylogic adopts the principle of closest distance evacuation, so that each pedestrian can leave through the exit closest to him or her. The experimental results show that the average accuracy of the YOLOv5s target detection model incorporating the SE attention mechanism can reach 94.01%; the constructed Anylogic emergency evacuation model can quickly provide an evacuation plan to guide pedestrians to leave from the nearest exit in an emergency, effectively verifying the feasibility of the method. The method can be extended and applied to research related to the construction of emergency evacuation aid decision-making systems in field stations.