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Issue title: Fuzzy logic systems for transportation engineering
Guest editors: Dalin Zhang, Sabah Mohammed and Alessandro Calvi
Article type: Research Article
Authors: Chen, Hongxua; * | Huang, Xingjianb | Li, Huana | Zhang, Haiboa
Affiliations: [a] School of Rail Transportation, Southwest Jiaotong University Hope College, Chengdu, China | [b] School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China
Correspondence: [*] Corresponding author. Hongxu Chen, School of Rail Transportation, Southwest Jiaotong University Hope College, Chengdu, China. Tel: +86 15281018495; E-mail: [email protected].
Abstract: Urban rail transit station has a large number of people gathering and relatively closed space, which has become a high incidence of emergencies. In the process of emergency evacuation, due to the unbalanced utilization rate of exits, the evacuation time is prolonged, which seriously threatens the safety of people in the station. In order to find out the reasons for the imbalance of the utilization rate of the exit, and put forward the solution, balance the utilization rate of each exit, improve the evacuation efficiency. In this paper, a subway station platform in Southwest China is taken as an example to establish a three-dimensional simulation model by using anylogic software. Through in-depth analysis, it is found that the reason for the unbalanced utilization of the platform floor exit is that the number of evacuation people at each exit does not match the evacuation capacity. According to the analysis results, the optimization model is put forward. Through comparative analysis, it is found that the optimization model can effectively balance the export utilization rate. Under the current conditions of off peak passenger flow, peak passenger flow and long-term peak passenger flow, the evacuation time can be saved by more than 20%.
Keywords: Urban rail transit, emergency evacuation, export utilization, evacuation time, anylogic
DOI: 10.3233/JIFS-219003
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 4, pp. 5181-5189, 2021
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