In order to reduce the following error of traditional pure pursuit algorithm, a Stanley compensatory pure pursuit algorithm is proposed. The simplified model of intelligent vehicle is established, and the front wheel angle compensation is used to ensure that the intelligent vehicle follows the expected path accurately. The simulation results show that the improved following control algorithm is effective, the maximum, average and standard deviation of the following error are reduced by 64.23%, 39.52% and 27.47% respectively. The simulation results show that the robustness of the improved pure pursuit algorithm is enhanced, and the intelligent vehicle can achieve stable, reliable and high precision tracking control effect.

In order to make the intelligent vehicle run safely and improve the applicability of local path planning algorithm in intelligent vehicle, the paper presents a local path planning method for intelligent vehicles. Firstly, establish vehicle model of Ackerman steering. In addition, the minimum turning radius constraint is added to the speed screening mechanism based on the traditional dynamic window approach. Then, in order to avoid excessive changes in the driving speed of intelligent vehicles, the curvature retention evaluation index is added to the evaluation function. The simulation results show that the improved algorithm meets the requirements of intelligent vehicle dynamic obstacle avoidance and can plan a safe and reasonable path.