Research And Application Of Improved A^* Algorithm And Ant Colony Algorithm In Parking Space Guidance System

In recent years,with the rapid improvement of China’s economic level,the number of private cars in large and medium-sized cities has become more and more.It is difficult to find parking space and road congestion has become a major problem in today’s society.Although the relevant vehicle management departments of the government have attached importance to this problem and put forward many practical schemes in the standardization and road governance of large parking lots,there are still problems such as the lack of timely access to parking information and the shortage of free parking Spaces,which result in drivers wasting a lot of time looking for parking Spaces.This problem can be effectively alleviated by applying the improved path optimization algorithm in parking space guidance system.The main research contents are as follows:First of all,this paper expounds the far-reaching significance of using Internet of Things technology to establish parking space guidance system,and briefly introduces the basic knowledge of Internet of Things and related path planning algorithm.Secondly,ant colony algorithm is selected as the solution of optimal parking space among many intelligent optimization algorithms in this paper,the key lies in the dexterity of this algorithm.Aiming at the design of parking space guidance module in the system,this paper proposes A method combining improved A*algorithm and ant colony algorithm to solve the optimal parking space.Because the convergence speed of ant colony algorithm is slow in the early stage of operation,this paper uses the improved A*algorithm to configure the initial pheromone of ant colony algorithm to improve the convergence speed.In consideration of the actual optimal parking space selection process will be affected by many factors.In this paper,by analyzing the factors affecting the parking time under the premise of a certain parking distance,the reference value of pheromone update is converted from parking distance to parking time,and the matrix of the shortest parking path and the shortest time for the vacant parking space is constructed.The model size,parking path distance,type of parking space and orientation of parking space are considered comprehensively as the updated pheromone of the improved ANT colony algorithm,so that it not only reflects the distance relationship of parking space,but also has directional guidance.This algorithm can improve the convergence speed and avoid local optimum.Finally,the improved A*algorithm and Ant colony algorithm proposed in this paper are applied to the parking space guidance system.According to the requirements of the system,the associated data table structure applied by the system is designed and the parking space guidance system is implemented.The parking space guidance system is developed by using Java and Matlab programming language,and the realization of various functions of the system is tested,which verifies the feasibility of the research results of this paper in the system.