Trajectory planning and tracking control of unmanned ground vehicle leading by motion virtual leader on expressway

Abstract

Abstract Formation driving can effectively solve the problem of driving efficiency and safety of unmanned ground vehicles (UGVs) on expressways. This study introduces a trajectory planning and tracking control method from initial position to its motion virtual leader in formation driving. In order to reduce the disturbance to the surrounding UGVs, trajectory planning is divided into two stages: steady speed tracking stage and parameter value matching stage. A tracking controller combined with a trajectory planner is designed to track the reference trajectory accurately. To ensure calculation speed and accuracy, a nonlinear model‐predictive control model is used in the trajectory planner, and the tracking controller is based on the linear time‐varying model‐predictive control (LTV MPC) model. Simulations are carried out with Carsim and MATLAB/Simulink, and the simulation results and comparative analysis show that the planned trajectory is feasible and can effectively avoid static and moving obstacles. Compared with the Stanley controller, the LTV MPC controller has the advantages of faster convergence speed, better stability and accurately tracking.

Keywords

• Spatial variables control
• Road‐traffic system control
• Mobile robots
• Stability in control theory
• Optimal control
• Time‐varying control systems