面向异构车辆的统一运动规划方法

Under the unified algorithm framework, by incorporating the unique motion characteristics of heterogeneous vehicles to generate differentiated planning results, a motion planning method based on generating and selecting behavior primitives is proposed. First, a primitive optimization generation problem that integrates driving behavior data and vehicle kinematics model is constructed. By establishing driving behavior constraints with spatio-temporal coupling information, based on the primitive category and its own longitudinal and lateral coupling laws, the optimal generation of the behavior primitive library is completed. Secondly, under the unified behavior primitive extension and selection framework, the primitives are selected from the behavior primitive library, associating as the behavior primitive sequence, generating the motion planning results coupled with trajectory and velocity. Finally, in the unstructured scene, the actual experimental research of the wheeled and tracked vehicle platforms is carried out. The results show that the proposed unified motion planning method for heterogeneous vehicles can generate motion planning results, reflecting the differences in the characteristics of heterogeneous vehicles, benefiting from the diversity of primitives in the behavioral primitive library and the richness of the information covered.