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

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.