Research On Path Planning Strategy Of Intelligent Vehicle Based On Improved A-star Algorithm

The emergence of intelligent driving vehicles not only promotes the development process of vehicles,but also provides solutions for today’s frequent traffic accidents and road congestion.Path planning and trajectory tracking are the basic functions of vehicle autonomous driving,which have been deeply studied in this paper.Path planning mainly includes two contents: environment modeling and path search.This paper firstly introduces several common environment representation and path search algorithms,from which selecting a grid map environment representation and a heuristic algorithm based on graph search.Among them,A-star algorithm as a global path planning algorithm,the search path length is globally optimal,but,there being many intermediate nodes,and the search efficiency is not high.Therefore,it comes up with improving the search method of traditional A-star algorithm.The simulation results showed that the improvement effect is obvious;Secondly,A-star algorithm in the complex environment to search the path is not smooth enough,the lack of vehicle state information,also vehicles cannot follow the planned trajectory.The improved A-star algorithm is integrated with the dynamic window algorithm.The fusion algorithm is a "global + local" planning algorithm,which considers the constraints of the vehicle.It can guarantee the global optimization and certain smoothness of the trajectory,also can be directly used for trajectory tracking.For the trajectory tracking of intelligent vehicles,a trajectory tracking controller based on model predictive control is designed based on vehicle model.The optimal solution of the prediction model is given by combining the objective function and constraint conditions.The tracking effect of the controller was verified under the linear condition.In order to reduce the calculation,the traditional algorithm usually sets the longitudinal speed of the vehicle as a fixed value,which has a good tracking effect at low speed.But with the increase of vehicle speed,the vehicle handling stability becomes worse.In order to ensure the safety and stability of the vehicle,the speed adaptive adjustment is added on the basis of the traditional algorithm,and the algorithm effect was verified at different speeds.Finally,the grid map is established based on the real road environment,and the path planning and trajectory tracking are combined.The effectiveness of the algorithm was verified by the co-simulation of MATLAB / Simulink and CarSim.