Real-time motion planning of self-driving vehicle on closed structured road

Abstract

Automated driving motion planning algorithms require a high degree of real-time performance. In a closed structured road environment, making full use of the road information helps to reduce the computational effort and improve the real-time performance of the algorithm. Therefore, this paper proposes a real-time automated driving motion planning process suitable for closed structured road environments. Based on the environmental information of the structured road, the key factors affecting the motion decision are extracted. The scenarios are classified according to the key factors, and decision rules are established for the vehicle based on the headway. In addition, based on a pure tracking algorithm, a motion planning method based on dynamic target points is proposed, which takes into account both single-cycle trajectory planning and vehicle motion continuity. Finally, a real-vehicle test is conducted under two typical driving scenarios. The results show that the proposed motion planning process has a good real-time performance and adaptability in real traffic scenarios.