Research On Evacuation Simulation And Path Optimization Of Subway Station Personnel Under Emergency

With the development of urbanization in China,urban rail transit system represented by subway has become an indispensable part of urban transportation system.At present,large passenger flow has become the normal operation state of many subway stations.In the case of large passenger flow,on the one hand,the subway station is prone to emergencies;on the other hand,the evacuation of subway personnel is extremely difficult,and the consequences caused by improper handling are extremely serious.Reasonable evacuation route optimization of subway station is an important means to reduce casualties in emergencies.In order to meet the needs of the emergency evacuation of public facilities in China and ensure the rapid and efficient evacuation of people in emergencies.In this paper,based on the background of subway station emergency evacuation,based on the theoretical knowledge of safe evacuation,crowd evacuation behavior and intelligent optimization algorithm,the simulation software is used to analyze the evacuation process of subway station.Considering the factors of time,congestion and disturbance,the multi-objective model of subway station evacuation path optimization under emergency is constructed,and the improved quantum ant colony algorithm is used the method can be used for reference in the study of subway station evacuation.The main research work in this paper is as follows:Firstly,taking the emergency evacuation in public facilities as the theme,the evacuation models and solutions at home and abroad are summarized and analyzed.On the basis of theoretical research and taking a metro station in a city as the background,the simulation model of personnel evacuation in the metro station is constructed,and some suggestions for improvement are put forward.This part of work shows that simulation technology plays an important role in the field of subway station evacuation research and the importance of building evacuation path optimization model considering congestion,which provides the basis for the relevant parameters setting in the later chapters of the paper.Secondly,considering the adverse effect of the congestion on the psychological behavior of evacuees in the actual evacuation process,the concept of crowding degree is defined,and a multi-objective evacuation path optimization model is established based on the premise of the shortest total evacuation time and the minimum cumulative crowding degree of each road section.The improved quantum ant colony algorithm is used to solve the model,and a more realistic and time-efficient evacuation path can be obtained.Finally,an improved quantum ant colony algorithm is designed by combining the idea of quantum evolutionary algorithm with the ant colony algorithm.The algorithm system is improved from the distribution of initial pheromones,the release of pheromones in different sections and the introduction of mutation strategy.The improved algorithm of mixed strategy can absorb the advantages of other algorithms and make the new algorithm more perfect.By solving the improved evacuation path optimization model with the new algorithm,the optimal evacuation path in different situations is found,and the algorithm is compared with other swarm intelligence algorithms.