Geometric path tracking algorithm for autonomous driving in pedestrian environment

This paper proposes an alternative formulation to the pure pursuit path tracking algorithm for autonomous driving. The current approach has tendencies to cut corners, and therefore results in poor path tracking accuracy. The proposed method considers not only the relative position of the pursued point, but also the orientation of the path at that point. A steering control law is designed in accordance with the kinematic equations of motion of the vehicle. The effectiveness of the algorithm is then tested by implementing it on an autonomous golf cart, driving in a pedestrian environment. The experimental result shows that the new algorithm reduces the root mean square (RMS) cross track error for the same given pre-programmed path by up to 46 percent, while having virtually no extra computational cost, and still maintaining the chatter free property of the original pure pursuit controller.