Autonomous Vehicle Path Planning Considering Dwarf Or Negative Obstacles

Autonomous vehicle path planning involves finding a collision-free and kinematic-feasible path from the start to the goal. Evidently, collision-free and kinematic-feasible are the two most important parts of the path planning process. In this paper, we propose a collision checking method that considers dwarf or negative obstacles, which can improve the traversability and stability under the promise of ensuring collision-free, and we use a kind of motion primitives which considering non-holonomic constraints for path planning to generate a kinematic-feasible path. Specifically, some existing approaches of collision checking deal with lofty and dwarf obstacles, or wide and narrow, negative obstacles in the same manner that require the entire vehicle body to steer away from them. However, some dwarf obstacles are shorter than the chassis of the vehicle while some negative obstacles are narrower than the vehicle track. In those cases, overstriding maneuvers will prove much more efficient and reasonable. Moreover, dealing with these obstacles in the same way as lofty obstacles can dramatically reduce the flexibility and disturb the stability of path planning under clustered environments, especially when the vehicle moves at higher speed. This paper proposes a double layer collision checking (DLCC) method that deals with lofty and dwarf obstacles, or wide and narrow, negative obstacles separately, effectively increasing the flexibility under the complex scenarios where dwarf and narrow negative obstacles exist.