Real-time Local Path Planning for Intelligent Vehicle combining Tentacle Algorithm and B-spline Curve

Abstract

The obstacle-avoidance problem of intelligent vehicles is one of the challenges that we face in path planning. In order to tackle it, this paper proposes a real-time path planning approach based on tentacle algorithm and B-spline curve. In this approach, firstly, some virtual tentacles are built to represent the precalculated paths of the ego vehicle at a current speed. Secondly, it selects the best tentacle path among them, which is required to provide a safe driving direction and sampling area for generating B-spline paths. When the vehicle drives along the best tentacle path, the B-spline path is generated according to the sampling area. Finally, the designed path is formed by segments of the best tentacle and a B-spline curve. Compared with other sampling-based path sets approaches, using the proposed approach needs shorter reaction time. Simulation and experiment results verify the real-time performance and effectiveness of the algorithm of local path planning.