Research On Obstacle Avoidance Path Planning And Horizontal Control Of Visual Navigation Intelligent Vehicle

Intelligent car as an important part of intelligent transportation system,the development of intelligent vehicles can not only reduce the occurrence of traffic accidents,but also in the industrial,emergency relief,military space and other fields have a broad space for development.So as an important part of intelligent transportation system intelligent car has become the focus of people's research.Path planning and path tracking control is the key technology of intelligent vehicle research,which is the key to realize the driving of intelligent car.In the study of intelligent vehicle path planning and path tracking control,how to plan a path to meet the requirements and how to realize the control of intelligent vehicle steering in the environment with obstacle has become a hot and difficult problem.Therefore,this paper takes visual navigation intelligent vehicle as the research object to study its obstacle avoidance path planning and horizontal control.Artificial potential field method has the advantages of simple structure,small computation amount and good real-time performance.Therefore,the artificial potential field method is chosen as the intelligent vehicle obstacle avoidance path planning algorithm.The traditional artificial potential field obstacle avoidance model is established.The simulation results show that the traditional artificial potential field method is not smooth.Therefore,based on the vehicle linear two-degree-of-freedom differential equation,the traditional artificial potential field method is improved according to the safety limit and steering characteristic of the intelligent vehicle.The simulation results show that the improved artificial potential field method is more smooth.In the past,the research on the lateral control of intelligent vehicle adopts feedback control,which cannot take advantage of the future environmental information,and the shortcomings of intelligence and robustness in control and planning.Therefore,the trajectory tracking control strategy of visual preview is used to fuse the lateral deviation and azimuth deviation obtained by the visual preview model.The fuzzy controller is selected as the intelligent vehicle lateral controller,and the change rate of the fusion deviation and the fusion deviation is taken as the fuzzy controller input and the front wheel angle as the output to realize the steering control of the intelligent vehicle.According to the problem of road curvature mutation,the curvature of the intelligent vehicle is modified,and the curvature of the road is corrected based on the visual preview model.The effectiveness of the proposed fuzzy preview controller and the effect of the correction of the road curvature are simulated on the joint simulation platform composed of Simulink and CarSim,and the obstacle avoidance path is improved by improving the artificial potential field method.The robustness of the designed controller is simulated by changing the parameters of the vehicle.The simulation results show that the fuzzy preview controller has better path tracking control effect and has strong robustness.The road curvature correction algorithm is used to improve the stability of the vehicle in the curvature mutation path.