关键词: 自动驾驶；全局路径规划；迪杰斯特拉算法；封闭环境建模

Abstract: With the rapid development of autonomous driving technology, its key technologies can be divided into four modules: perception, decision, planning and control. Path planning plays an important role in them. A good path planning algorithm can plan an optimal path before automatic driving. In the process of driving, it can combine the environmental information sent back by perception and decision, and then plan a fine-tuned local path in real time. On the basis of completing functions such as obstacle avoidance and lane changing, the planning takes into account the safety and comfort of the driving trajectory. Based on Dijsktra shortest path planning algorithm, this paper starts with the discussion of global path planning and constructs a topological node map in a closed environment. Then improve the algorithm, which not applicable to the pain points in the real environment test of autonomous driving, so as to realize the global path planning task from any starting point to the end point. Finally, it is verified in the real vehicle test. The test results show that in a close and closed-loop environment, the self-driving vehicle can plan the ideal shortest path for driving.

Key words: Autonomous driving; Global path planning; Dijkstra algorithm; Closed environment construction