Obstacle avoidance path planning algorithm for intelligent vehicles on structured road

Aiming to address the obstacle avoidance issues of smoothness and real-time on structured roads for intelligent vehicles, a novel obstacle avoidance path planning algorithm is proposed which utilizes various curve fitting methods. The algorithm incorporates a cruise model that employs a third-order Bessel curve to splice sampled lane lines, generating cruise candidate paths. And in the lane change mode, quintic polynomial curves are used to generate lane change candidate paths. By simulation and experiment, the proposed obstacle avoidance algorithm is verified to be excellent in terms of obstacle avoidance and lane keeping in complex multi-obstacle scenarios on structured roads.