Local Path Planning for Intelligent Vehicle Obstacle Avoidance Based on Dubins Curve and Tentacle Algorithm

Local path planning for obstacle avoidance is one of the core topics of intelligent vehicle. A novel method based on dubins curve and tentacle algorithm is proposed in this article, with the consideration of obstacle avoidance and vehicle motion constraints. First, the preview distance of the vehicle is given according to the current speed, so that the preview point can be found with the information of global path. Then dubins curve is adopted to find a path with appropriate turning radius, between the current position and preview point, satisfying the constraints of current direction and target direction, considering handling and ride comfort of the vehicle. In order to avoid obstacle, tentacle algorithm is adopted. 20 tentacle points are given by moving the original preview point, and then 21 local paths can be given by using dubins curve. Cost function is used to find out the best option of the 21 paths. The distance to obstacle, the final distance to original preview point and the change of moving direction are taken into consideration in the cost function. By applying dubins curve and tentacle algorithm, a local path with obstacle avoidance and better vehicle handling can be obtained. Simulations have been carried out with the co-simulation of Matlab /Simulink and CarMaker. Results show that the vehicle can avoid the collision with static and moving obstacles. The vehicle trajectories were smooth, and the turning radius was kept in a suitable range to ensure the vehicle handling. Simulation results show that the proposed local path planning method can realize obstacle avoidance with good handling performance.