Research On Vehicle Obstacle Avoidance Path Planning Based On APF Algorithm

Autonomous driving technology has become the focus of the automotive field around the world.Decision planning,one of the key technologies of autonomous driving vehicles,is regarded as the prerequisite for autonomous driving vehicles to drive safely to the destination.The driving safety of the autonomous driving vehicle can driving safely based on the correct execution of the path planned by the decision command.The path with the purpose,safety and real-time requirements of vehicle driving in a complex dynamic environment,obtained by path planning should improve the ability to deal with emergencies as much as possible.The content of this paper: to study the feasibility and safety of artificial potential field algorithm for road driving of autonomous driving vehicles,the main contents are as follows:(1)The principle and existing problems of the traditional artificial potential field algorithm were introduced.Aiming at the local optimization problem of the traditional artificial potential field algorithm and the weak ability of dynamic path planning,the virtual water flow method and the repulsive potential field influence factor constructed by the distance between the vehicle and the target point were adopted to solve the local optimization problem of the traditional artificial potential field algorithm,and the velocity potential field was adopted to improve the dynamic path planning ability of the traditional artificial potential field algorithm.The results show that the improved artificial potential field algorithm can not only solve the local optimal problem,but also effectively avoid dynamic obstacles to complete path planning.(2)Based on the excellent local obstacle avoidance ability of the artificial potential field algorithm,the artificial potential field algorithm was applied to the vehicle-road scene to complete the vehicle local path planning.With reference to "JTG D20-2017 Highway Route Design Code" and "JTG B01-2003 Highway Engineering Technical Standard",the stopping sight distance was introduced into the road gravitational potential field to represent the distance between the vehicle and the central point of the current gravitational potential field.In addition,the multi-lane road repulsion potential field model,composed of the repulsive potential field centered on the road boundary line,the road dividing line and the road centerline,was proposed.Simultaneously,the repulsion potential field model of rectangular obstacle was established to represent the repulsion potential field of obstacle vehicles on the road.Finally,the artificial potential field algorithm based on vehicle-road was used to plan the lane-changing overtaking condition of the vehicle.The results show that under the joint action of road gravitational potential field,obstacle repulsion potential field and road repulsion potential field,vehicles can drive normally in the safe area of the lane and avoid obstacles to complete lane-changing overtaking path planning.(3)Track and control the vehicle path.Path tracking consists of two parts: for lateral path tracking control,firstly,a linear discretization prediction model was established based on three-degree-of-freedom bicycle dynamics model,"magic formula" tire model and linear discretization prediction model optimized by small angle theory of trigonometric function.Under the constraint conditions,the prediction model and objective function were used to solve the optimal state quantity and control quantity.Simultaneously combined with the approximate relation function of vehicle speed and prediction time domain,a variable time domain model predictive controller was established,and the previous wheel angle is used as the output.The longitudinal speed tracking controller was designed as a hierarchical structure.The upper PID controller takes the speed confidence error as the input and outputs the expected acceleration to the lower controller.The lower drive/brake mode controller performed drive/brake mode switching with the desired acceleration,outputs throttle opening control and brake pressure output,and realizes the tracking control of the desired speed.(4)The rationality of the tracking controller and the feasibility of the path obtained by the artificial potential field algorithm were verified.The longitudinal speed tracking control of the longitudinal speed controller was verified under the uniform acceleration and deceleration condition and the continuous slope variable speed condition.At the same time,the tracking performance of the lateral tracking controller was tested by the lane-changing path,and the tracking simulation test was carried out on the lane-changing overtaking path obtained by the artificial potential field algorithm.In the process of two lane changes,the tracking effect is poor,the lateral displacement error is less than 0.25 m,and the rotation angle of the front wheel is also within ±1.5 °.But it satisfies the lateral tracking control accuracy and vehicle constraints,so the lane-changing overtaking path is feasible.