Research On Intelligent Vehicle Path Planning Based On Improved Sparrow Search Algorithm

As one of the research hotspots in the field of intelligent vehicle driving control,path planning aims to find a safe,collision-free and low-energy path connecting the starting point to the end point in the search space.At present,most relevant research results of vehicle path planning were obtained by adjusting and improving vehicle path planning algorithms.In this paper,sparrow search algorithm was applied to solve such problems,and then problems existing in the application process were solved.The main research contents are as follows:(1)The analysis of commonly used swarm intelligence optimization algorithms show that the sparrow search algorithm has strong comprehensive performance,but there were problems such as weak convergence ability and insufficient ability to jump out of local optima.Firstly,the ICMIC mapping function was introduced for population initialization to improve the convergence and traversal capabilities of the algorithm.Secondly,improve the sparrow position update formula and optimize population redundancy operations to enhance the algorithm’s ability to jump out of local optima.Finally,use benchmark functions to test the performance of the improved sparrow search algorithm.(2)When using the improved algorithm to solve the path planning problem,in order to simulate the path planning process of an intelligent vehicle in a complex environment,two groups of environments with different spatial sizes were constructed,and each group was set up with three maps with increasing numbers of obstacles in sequence.The results show that in maps of different sizes,the improved sparrow search algorithm has improved the optimal path length,number of inflection points,and convergence speed compared to the original algorithm,indicating better performance in solving path planning problems.(3)When further considering the influence of geometric constraints on path planning,it was found that the optimal path was not sufficient to meet the requirements of vehicle geometry and driving characteristics.In order to solve the above problem,a path planning method incorporating optimization algorithm was proposed,using Bessel curves to optimize the path to ensure that the optimal path can meet the geometric constraints of the vehicle.Two different sets of tests were set up to verify the feasibility of the smoothing strategy,and the test results show that the driving trajectory after smoothing was better than the previous one in terms of both the number of nodes and curvature,which was more in line with the operation rules of the vehicle and can effectively ensure driving safety.