Collision-Free Path Planning with Kinematic Constraints in Urban Scenarios

In urban driving scenarios,owing to the presence of multiple static obstacles such as parked cars and roadblocks,planning a collision-free and smooth path remains a challenging problem.In addition,the path-planning problem is mostly non-convex,and contains multiple local minima.Therefore,a method for combining a sampling-based method and an optimization-based method is proposed in this paper to generate a collision-free path with kinematic constraints for urban scenarios.The sampling-based method constructs a search graph to search for a seeding path for exploring a safe driving corridor,and the optimization-based method constructs a quadratic programming problem considering the desired state constraints,continuity constraints,driving corridor constraints,and kinematic constraints to perform path optimization.The experimental results show that the proposed method is able to plan a collision-free and smooth path in real time when managing typical urban scenarios.