Research On Path Planning And Tracking Control Of Unmanned Vehicles Based On Improved Potential Field Algorithm

In recent years,China’s car ownership has increased significantly,the rapid development of the automobile industry has also brought a series of problems,such as traffic congestion,traffic accidents and other problems.The development of unmanned driving technology provides some new ideas to solve these questions.The unmanned driving technology mainly includes obtaining environmental information,path planning and trajectory tracking,among which path planning and trajectory tracking are the core issues of the unmanned driving technology.In this thesis,the feasibility of unmanned local path planning is studied and verified,the local path trajectory based on improved potential field method is constructed,and the trajectory tracking simulation is verified by model predictive control.The specific research contents are as follows:Firstly,the relevant algorithms of local path are introduced,the vehicle kinematics model and vehicle dynamics model are constructed respectively,and the vehicle kinematics model and dynamics model are described in detail and formula reasoning,which provides a theoretical basis for path planning and trajectory tracking.Secondly,the traditional potential field method theory is studied and analyzed,the advantages and disadvantages of the traditional potential field method are described in detail,and the traditional potential field method is improved as follows:according to the characteristics of driving vehicles and the constraints of road boundary,the road potential field function meeting the safe driving of vehicles is built,and the boundary repulsion force is established.The shape characteristics of obstacle vehicle are studied,and the obstacle boundary repulsion force more in line with the real vehicle is constructed.In view of the problem that the road curvature is too small to meet the normal driving of vehicles in previous studies,B-spline curve is introduced to restrict the curvature to meet the normal driving of vehicles.Thirdly,the model prediction is described in detail,the linearized error model is established and the objective function and constraint conditions are optimized.The trajectory tracking controller based on vehicle kinematics model and vehicle dynamics model was built,and the simulation verification was carried out in Matlab,and the tracking effect of the controller at different speeds was tested.Finally,the Carsim/Simulink simulation platform is built,and the nonlinear model predictive controller is modeled and simulated on the simulation platform,and the feasibility of the improved potential field method in path planning is verified.The results show that the local paths planned by the improved potential field method can satisfy the normal driving of the tracking vehicle.