Abstract: Aiming at cooperation problem of the human-machine collaborative assistance steering system, a shared steering predictive control method based on correlation analysis is proposed. In this method, the vehicle state and road information stored in memory buffer are used to analyze the correlation between the driver’s input torque and the assistance torque with probability statistics method. It is employed to assign the control authority, and incorporated into the predictive control design of assistant steering torque. At the same time, a real-time obstacle avoidance trajectory planning method is proposed for moving obstacles with uncertainty motion. The optimal trajectory can be obtained according to the change of obstacle trajectory and constraint conditions, and this trajectory can be used as target path tracked by the proposed human-machine cooperative prediction steering controller. The obtained results indicate that: the proposed human-machine shared predictive steering control method can provide the required torque according to the driver's torque characteristics and improve the collaborative steering performance with reduced driving workload. Additionally, it has better good tracking accuracy and vehicle stability performance. The proposed trajectory planning method can obtain optimal trajectory to avoid obstacles in real-time. Combined with the cooperative predictive steering control strategy, the optimal trajectory is tracked in real-time. It is finally formed as integrated trajectory planning and tracking control strategy with function of human-machine shared predictive steering.

Key words: torque correlation, steering assistance, trajectory planning, predictive control, human-machine collaboration