Research On Passenger Evacuation Path Planning In Large Airport Hub Based On Improved Ant Colony Algorithm

As a passenger hub with important functions for aviation transportation network and passenger transport,airport hubs have a closed and complicated internal structure that increases the possibility of emergencies,especially fires,which may cause significant loss of life and property.If a corresponding evacuation strategy is not developed in advance,the consequences will be difficult to estimate.Therefore,in order to reduce the loss of life and property caused by sudden fire incidents,this paper mainly focuses on studying the evacuation path of passengers in large airport hubs when fires occur using an improved ant colony algorithm.The main research contents are as follows:(1)Analysis of factors affecting passenger flow evacuation efficiency.Based on the indepth analysis of the types and characteristics of sudden accidents inside large airport hubs,this article focuses on analyzing the characteristics and potential risk sources of fires inside hubs,and summarizes the potential risk sources,accident causes,and accident consequences under different fire factors.After that,factors affect passenger flow evacuation efficiency under fire accidents are introduced in detail,including physical and psychological factors of passengers,fire product factors,and crowd density.The impact of heat radiation,toxic and harmful gases,smoke concentration in fire products,and crowd density on passenger evacuation speed were quantified,and the evaluation standards for passenger safety evacuation in large airport hubs were determined.(2)Research on evacuation path planning based on improved ant colony algorithm.This paper clarified the differences between fire evacuation path planning and other path planning problems,summarized the characteristics and applications of various path planning algorithms.On this basis,an improved ant colony optimization algorithm was proposed for fire scenes due to the algorithm’s robustness and scalability.The influence of fire products,path traffic,destination orientation,and crowd density are considered in the heuristic factor,and the geometric length of the path is replaced by an equivalent distance.The simulation of the grid model of Beijing Daxing Airport proves that the improved algorithm has faster convergence speed,it also has characteristics of feasibility and stability in finding optimal evacuation paths in complex environments.(3)Evaluation of the effectiveness of passenger evacuation route plans and analysis of evacuation bottlenecks based on the Any Logic secondary development method.After comparing the characteristics of different pedestrian flow simulation software,the Any Logic simulation software is used to construct an evaluation model for the effectiveness of passenger evacuation path plans in fire situations.Based on the survey data of Beijing Daxing International Airport,the passenger simulation logic process is built.Through the secondary development of Any Logic,the different behavior choices of passengers in case of fire are restored.The "one button switch" function is used to visualize the normal departure process of passengers and the emergency evacuation process in case of fire;The bar chart comparison proves that the shortest evacuation path proposed by the improved algorithm can save passengers’ walking time,and the effectiveness of the improved ant colony optimization algorithms is verified;Finally,by analyzing the bottlenecks in passenger evacuation through pedestrian density maps,improvement suggestions were proposed for the layout of software and hardware facilities.This study provides a scientific and effective evacuation path planning method for aviation hub managers,and proposes targeted evacuation suggestions to improve the efficiency of personnel safety evacuation in the event of a fire inside a large airport hub,ensuring the safe evacuation of passengers.