Research and Application of Obstacle Avoidance Path Planning Based on Hermite Curve Interpolation

With the development of sensor technology, artificial intelligence technology, and vehicle networking technology, autonomous vehicles have become an important member of the intelligent transportation system. And the path planning performance is one of the main parameters for evaluating the performance of intelligent driving vehicles, especially the path planning and control performance when facing obstacles. In order to improve the autonomous safety performance of intelligent driving vehicles facing obstacles in complex environments, this paper proposes an obstacle avoidance path planning method based on lane translation and Hermite curve, considering three types of constraints, such as vehicle dynamics constraints, comfort constraints, and global path constraints as the basic constraints for obstacle avoidance trajectories. The experimental results indicated that the obstacle avoidance traj ectory planned by this obstacle avoidance method meets the requirements of vehicle dynamics. It has good comfort, reasonable relationship with the global path, and user-friendly obstacle avoidance trajectory, achieving perfect avoidance of obstacles and the ability to return to the original reference path when encountering obstacles. It is a comprehensive and coordinated obstacle avoidance trajectory planning that enhances the active obstacle avoidance ability of intelligent vehicles.