Research On Autonomous Vehicle Path Planning Based On Improved A* Algorithm And Improved DWA Algorithm

The emergence of assorted new technologies and algorithms with higher performance currently give sturdy support for the event of driverless vehicles within the direction of unmanned and intelligent.Driverless technology is an imperative a part of the longer term intelligent town traffic designing,which might cut back the pressure of traffic and unnecessary traffic accidents to an explicit extent,adding to the development of a more robust society.As a neighborhood of driverless automobile technology,path designing is of nice analysis significance to United States of America.Based on the analysis of the status quo of unmanned vehicles and the induction and comparison of existing path planning algorithms,this paper chooses a dual path planning idea,and proposes a combination of improved A* global path planning algorithm and improved DWA local planning algorithm Improve the idea,and verify through multiple sets of simulation experiments that the improved algorithm can plan a feasible global path more efficiently.The main research contents of this paper are as follows:(1)It explained the background and significance of the topic,and learned about the development of foreign unmanned driving through relevant materials.After summarizing several path planning algorithms that I know,I analyze their characteristics.(2)Perform a comprehensive and detailed anatomy of the A* algorithm from the root of it,and find that its search accuracy and speed are not high,and the planned path is not tangent to the obstacle vertices;(3)Aiming at the fact that the traditional DWA algorithm in local path planning is easy to fall into the local optimal solution,which leads to the side length of the global planning path;and when encountering unknown obstacles,the planned path cannot avoid obstacles in time,a design is designed.An improved dynamic window algorithm for multi-purpose nodes.Improve the smoothness of the path and the ability of local obstacle avoidance to a certain extent.Through the final fusion simulation experiment comparison,it can be seen that the improved algorithm has certain advantages.