Research On Path Tracking Control Of Intelligent Vehicle Under Large Curvature Conditions

In the era of comprehensive intelligence,intelligent vehicles have become a hotspot of integration research on traditional machinery manufacturing,automatic control,and information technology.It is also a key step in solving the problems of traffic safety,traffic efficiency and reducing traffic pollution.Motion control technology is the final execution stage of other key technologies of intelligent vehicles.Among them,the path tracking accuracy and driving stability issues on high-curvature roads affect driving safety and riding comfort,which is directly related to the landing of intelligent driving technology and acceptance by people.Based on the research funded by the National Key R&D Program of China(2018YFB1600701): Development and application of new multifunctional intelligent vehicle terminal,under the condition of large curvature road driving,the research on the path tracking motion control of intelligent vehicles is studied.First,establish intelligent vehicle kinematics model and two-degree-of-freedom dynamic model.For low-speed driving conditions,taking into account the requirements of lateral motion and longitudinal speed control,a path tracking strategy that can adapt to low-speed and largecurvature driving conditions is designed.Under medium and high speed driving conditions,considering the requirements of driving stability and path tracking accuracy,a path tracking strategy under medium and high speed driving conditions with large curvature is designed.Secondly,research on path tracking control under low speed and large curvature driving conditions,design intelligent vehicle motion control algorithm.In lateral motion control,a dynamic path planner is designed based on a fifth-order Bezier curve,a steering angle feedforward controller is established,and a PI feedback controller is established based on position deviation and heading angle deviation,and a preview distance function is designed considering longitudinal speed and position deviation.In longitudinal speed control,the speed decision model is established by considering the road curvature and pavement adhesion coefficient of the preview point,a layered speed controller is established,and the upper layer controller uses an integral separation PID algorithm.The throttle opening and brake master cylinder pressure are obtained in the lower controller based on the inverse longitudinal dynamics model.Next,research on path tracking control under medium and high speed and large curvature driving conditions,and design a lateral motion control algorithm based on particle swarm optimization.Establish a single-point preview dynamic model and its control state equation,design an improved sliding mode variable structure lateral motion controller.In order to make the system quickly reach the vicinity of the switching surface and reduce the chattering phenomenon,a new approach law based on improved double power is selected.By solving the sliding mode equivalent control quantity as the steering angle of the intelligent vehicle.The optimal preview distance algorithm based on particle swarm optimization is designed.The analytic hierarchy process is used to determine the weight coefficient of each index of the fitness function to achieve the optimal selection of the preview distance under different road curvatures and longitudinal speeds.Finally,establish a MATLAB/Simulink and Car Sim joint simulation platform and perform simulation verification.Construct low-speed and large-curvature roads and medium-high-speed and large-curvature road driving conditions,and simulate the two path tracking motion control algorithms designed in this paper under their corresponding driving conditions.