Research On Urban Emergency Rescue Path Planning Based On Ant Colony Algorithm

Modern cities have complex structures and large populations.In modern city life,various emergencies inevitably occur due to various natural factors such as earthquakes.When urban emergencies occur,they may encounter damage to the urban environment,building collapse,bridge-induced road disruptions,etc.,endangering the survival of the population and a large number of people waiting for rescue.To achieve the most efficient rescue of the people,a strong rescue force and a scientifically planned rescue path are needed,where the scientifically planned rescue path is the key to ensure the effective implementation of subsequent rescue operations,so how to scientifically and reasonably plan the rescue path of the people is of great importance.This thesis takes a city as the research object,and studies the vehicle path planning problem in the city under the emergency rescue environment,dividing the path planning problem into two cases: the path planning problem after the first emergency and the path planning problem after the second emergency.In these two cases,the urban road network is damaged respectively,which has an impact on the vehicle traffic and requires the planning of paths that can be passed.In order to judge the quality of the paths generated by the algorithm,three path evaluation metrics,namely the number of path entries,path length and repetition rate between paths,are proposed.The paper aims to solve the paths that can satisfy the requirements of the three metrics.The paper uses heuristic rules and basic ant colony algorithm as the main algorithms for solving.For the heuristic rule,linear function and softmax function are proposed as the state transfer function,respectively.For the ant colony algorithm,according to the actual background of the path planning problem under study,two improvements of improved selection strategy and improved pheromone update are made to the basic ant colony algorithm,so that the ant colony algorithm can achieve the effect of covering a larger range of road networks and finding shorter paths in the process of path planning.The experimental results confirm that both the heuristic rule and the ant colony algorithm used in this thesis can plan paths that satisfy the evaluation index and the algorithms are effective.Further by comparing the performance of the heuristic rule,the basic ant colony algorithm and the improved ant colony algorithm through comparative experiments,it is concluded from the experimental data that the performance of the improved ant colony algorithm is better than that of the basic ant colony algorithm,and the improved ant colony algorithm is more suitable for the path planning problem of emergency rescue vehicles after the occurrence of emergencies studied in this thesis.From the perspective of practical problems,this thesis proposes a solution to the emergency rescue vehicle path planning problem that can play a role and provide some reference for emergency rescue decision makers.