Research on smart car motion planning algorithm based on RRT

Aiming at the RRT algorithm's strong randomness, the obtained path is not the shortest, and the vehicle differential constraints are not satisfied, this paper proposes an improved RRT smart car motion planning algorithm. In a priori information environment where the map is known, a reasonable metric function that satisfies the vehicle kinematics constraints is proposed, so that the path is smoother and facilitates the optimization of the back-end trajectory. In addition, a pruning optimization method that reduces path nodes and shortens the path length is also proposed. The simulation results show that the improved RRT algorithm has a smoother path than the basic RRT algorithm, with fewer path nodes and a shorter path length. Finally, a collision-free, smooth and continuous trajectory that satisfies the vehicle movement is obtained.