Motion Planning For Automated Vehicles In Urban Areas

With the rise of intelligent technology,autonomous driving technology began to develop rapidly.Today,traditional car companies,research institutions,technology companies and emerging startups are the major players in the autonomous driving industry.Urban roads,as the main road scenarios to be dealt with by vehicles,are characterized by complex traffic conditions and large traffic flow.The application of intelligent driving technology can effectively improve road traffic safety,traffic efficiency and reduce traffic operation costs under urban road scenarios.The existing motion planning methods for structured roads in urban scenarios mainly consider lane changing strategies and local obstacle circumnavigations,but fail to comprehensively consider multi-objective constraints such as road speed limit,comfort and schedule constraints(for urban public transport).In addition,for the motion planning of unstructured(semi-structured)road scenes such as parking lots,it is difficult to give consideration to the rationality and efficiency of the planning.This paper aims to break through the motion planning methods of autonomous driving vehicles in structured and unstructured road scenarios under typical urban conditions.The main research contents of this paper include:Aiming at motion planning in structured road environment,a global trajectory planning method with path and velocity decoupling and a multi-layer sampling local trajectory planning method based on fixed sampling and polynomial curve fitting were proposed.Firstly,for the global trajectory planning in structured road environment,a global path smoothing method and a global velocity planning method considering the multi-objective constraints are proposed.The parameterized representation and smoothing processing of the path are carried out by using parameter ized splines and the optimization method based on quadratic programming to improve the smoothness of the global path.According to the optimized global path,the iterative optimization model of the global velocity was constructed by combining the trapezoidal velocity planning method with gradient descent method.The global velocity curve,which could satisfy the speed limit of the road,the constraints of the running schedule and the comfort constraints,was solved for the global path.By combining the global path with the global velocity curve,the global trajectory of the vehicle is obtained.Secondly,for the local trajectory planning of the structured road environment,a local trajectory planning method with fixed sampling and polynomial curve fitting were proposed,the method based on global trajectory respectively to track the longitudinal velocity,lateral offset and multiple sampling trajectory length,by polynomial curve fitting hopson as candidates for local trajectory;Finally,the cost function is established according to the comfort,safety and vehicle dynamics constraints,and the optimal local trajec tory is selected.Aiming at motion planning in unstructured road environment,a path planning method in open area combining improved hybrid A* graph search algorithm and "S-CS" parking model was proposed.Firstly,A path search algorithm based on the combination of generalized voronoi diagram and hybrid A* algorithm is proposed,and the passable path network is constructed from generalized voronoi diagram.According to the passable path network,the guide path is generated and the heuristic function of hybrid A* algorithm is designed to improve the efficiency and quality of path search.Secondly,to solve the problem that the global path generated by the graph search algorithm cannot accurately reach the target configuration(the position and Angle of the target point),an "S-C-S" parking model is proposed.A parking path composed of straight lines and arcs is generated by analytic formula to reach the target configuration accurately.It is convenient and practical to use the "S-C-S" parking model to plan the parking path.The characteristic that the straight line is taken as the end of the parking path is also more conducive to the parking path tracking of the control layer.The third task of this paper is to implement the algorithm and carry out simulati on tests in the MATLAB software environment,and carry out real vehicle tests on the actual urban roads,respectively to verify the effectiveness of the proposed urban structured road and unstructured road motion planning algorithms.The experimental results show that the motion planning method proposed in this paper can plan safe and effective driving trajectories in all urban road scenarios.