Hybrid A*-based Curvature Continuous Path Planning in Complex Dynamic Environments

Abstract

With the progress of autonomous driving technology in recent years, motion planning has been an issue in the navigation of self-driving cars. To achieve an optimal path that meets the requirements of both smoothness and safety, vehicle kinematics and dynamics constraints should be considered. This paper proposes a novel motion planning method based on Hybrid A* for real-time and curvature-contentious path planning with local post smoothing in complex dynamic environments: (1)our method introduces parametric clothoid curves precomputed offline as basic motion primitives for rapid online planning; (2)the path obtained using our method is G2-continuous (i.e., curvature continuous) and does not have a considerable effect on the search time consumption, while also considering possible collisions and motion constraints of nonholonomic car-like vehicles; (3) the node re-expansion issue of conventional Hybrid A* is discussed and resolved by the proposed quintic spine-based local smoothing approach for complete path continuity. Hence, post smoothing and collision checking for the overall resulting path. Simulation and on-road tests have been performed to evaluate the efficiency of the proposed method. The method can be widely implemented in numerous complex scenarios.