Local Path Planning And Tracking Control For Unmanned Trucks In Different Road Environments

Unmanned vehicles are a key area for the development of intelligent manufacturing in the future.With the rapid development of the domestic logistics industry and the reduction of the number of drivers,the voice of unmanned trucks is becoming increasingly high.Driven by cutting-edge technologies such as 5G,artificial intelligence,and high-precision sensors,domestic and foreign host manufacturers have listed unmanned trucks as important development goals.Planning control is particularly important for the ride comfort and safety of unmanned vehicles.A dynamic model of an unmanned truck is established,and the forces and moments acting on the truck in the lateral,longitudinal,and yaw directions are analyzed.A tire model is established based on magic formulas.The relationship between tire lateral force,lateral force,tire sideslip angle,and slip ratio under different load conditions is analyzed,providing theoretical guidance for the design of MPC controllers.The fourth order Bezier curve formula is derived and applied to lane change path planning for unmanned trucks in structured road environments.Curvature constraints,side slip,roll constraints,and safety distance constraints are added.The safe lane change interval is analyzed,and the lane change trajectory is optimized.For the path planning of unmanned trucks on unstructured roads,a fusion of JPS algorithm and Bezier algorithm is proposed,which optimizes the inflection points of JPS algorithm path planning and improves the smoothness of the path.An active steering controller based on MPC is designed for tracking different vehicle speeds and load conditions;The longitudinal control is divided into two layers.The upper layer performs longitudinal speed tracking based on model predictive control theory,and the lower layer inversely solves the throttle opening based on the torque rotational speed throttle opening curve,giving the desired braking deceleration,thereby determining the brake master cylinder pressure,and achieving transverse and longitudinal control.Finally,a joint simulation platform was built to compare the lane change tracking effects of LQR,PID,and MPC controllers.A double lane change tracking simulation experiment was designed to verify the stability of trajectory tracking for unmanned trucks under different operating conditions.