自主车辆路径规划算法研究

在自主车辆的路径规划是否经过特定点的两种实际情况下,提出了不同的解决方案。当车辆不需要经过特定点时,引入A*算法,较传统算法将启发函数改为欧几里得函数(Euclidean Distance),并引入一个权值以降低启发函数的权重。当车辆需要经过特定点时,应用Hopfield神经网络思想优化算法,以达到理想的路径规划。仿真实验表明,改进后的算法使得路径规划寻优得到明显提高,并验证了算法的有效性。

Path Planning Algorithm for Autonomous Vehicle

In this paper, path planning of autonomous vehicles through a specific point of whether the actual situation of two, which proposed the respective solution: a certain point without the need for global planning, conditions of heuristic, compared with traditional A* algorithm, is equaled with euclidean distance,and add a weight which reducing the importance of heuristic relatively.In the other opposite planning , the hopfiled neural network is adopted in order to achieve the desired path planning. The simulations show that the improved algorithm enhances the performance of path planning, and proved the validity of the algorithm.