The application discloses an automatic driving path planning
obstacle avoidance method and
system based on sampling and
cost evaluation. The method comprises a spline
curve fitting step, a path sampling step, a sampling
path cost calculation step, an optimal path determination step and an optimal path speed planning step. The spline
curve fitting step determines control points and curve parameters through specific calculation to obtain a discrete path. The path sampling step calculates and splices three sections to generate multiple candidate sampling paths with smooth transitions. The sampling
path cost calculation step evaluates
path cost from multiple dimensions such as longitudinal, transverse and lane changing and comprehensively calculates. The optimal path determination step selects an optimal path according to the
cost evaluation result. The optimal path speed planning step optimizes the speed according to the obstacle collision situation. The application solves the problems of slow running speed, low planning success rate and non-smooth trajectory of the existing
algorithm, improves the efficiency, success rate and stability of automatic driving path planning
obstacle avoidance, is suitable for the automatic driving technical field, promotes the development of automatic driving technology, and effectively improves the
driving safety and reliability of automatic driving vehicles in various complex environments.