Unmanned Vehicle Motion Control And Autonomous Parking Path Planning

With the rapid development of artificial intelligence technology,unmanned driving is used in various fields such as military,commercial,and civilian use.It shows great vitality and provides a solid guarantee for national security and social convenience.In order to ensure the safety and smoothness of unmanned vehicles during driving,the trajectory tracking control technology of unmanned vehicles appears Increasingly important,it has become the focus of scholars’ research.At the same time,in order to achieve a complete driverless system,the autonomous parking module has become an indispensable part.As a sign of high automation,the purpose is to complete the specific parking area without human intervention.Fully autonomous driving operation in the scene.This paper conducts related research on unmanned vehicle trajectory tracking control and autonomous parking technology.The main tasks are as follows:An unmanned system platform was built on the wire-controlled chassis of Ackerman structure to verify the feasibility of related algorithms.The platform is equipped with Global Navigation Satellite System(GNSS),Inertial Measurement Unit(IMU),lidar,visible light camera,etc.We complete the data transmission within the system through a custom data format and design the QT interface to monitor the sensor data and vehicle status information in real time.For unmanned vehicle trajectory tracking,longitudinal control and lateral control are used to track the unmanned vehicle’s speed and position of desired trajectory.Longitudinal control is based on Proportion-Integral-Differential(PID)closed-loop controller and the open loop calibration table to complete the control of the accelerator and brake of the vehicle;Lateral control completes the identification of relevant parameters on the basis of the vehicle steering model,and constructs a curvature compensation feedforward control and Linear Quadratic Regulator(LQR)optimal feedback control to complete the control of the wheel angle.The actual vehicle test in the campus environment can complete the trajectory tracking task well and the feasibility of the control system is verified.A Hybrid A* autonomous parking path planning method based on the guidance of artificial potential field is proposed.In view of the high computational efficiency of the artificial potential field algorithm and the fact that Hybrid A* algorithm has the characteristics of vehicle nonholonomic constraints,the advantages of the two algorithms are complementary.The direction information of the artificial potential field is used to guide the node expansion of the Hybrid A* algorithm,Compared with a single algorithm,it can quickly plan a driving path that meets the vehicle kinematics constraints.