High‐level decision‐making for autonomous overtaking: An MPC‐based switching control approach

• Published in: IET intelligent transport systems 2024-07, Vol.18 (7), p.1259-1271
• Main Authors: Wang, Xue‐Fang, Chen, Wen‐Hua, Jiang, Jingjing, Yan, Yunda
• Format: Article
• Language: English
• Subjects: automated driving and intelligent vehicles; autonomous driving; decision‐making; optimal control; predictive control; switching systems (control)
• ISSN: 1751-956X; 1751-9578
• DOI: 10.1049/itr2.12507

The key motivation of this paper lies in the development of a high‐level decision‐making framework for autonomous overtaking maneuvers on two‐lane country roads with dynamic oncoming traffic. To generate an optimal and safe decision sequence for such scenario, an innovative high‐level decision‐making framework that combines model predictive control (MPC) and switching control methodologies is introduced. Specifically, the autonomous vehicle is ed and modelled as a switched system. This ion allows vehicle to operate in different modes corresponding to different high‐level decisions. It establishes a crucial connection between high‐level decision‐making and low‐level behaviour of the autonomous vehicle. Furthermore, barrier functions and predictive models that account for the relationship between the autonomous vehicle and oncoming traffic are incorporated. This technique enables us to guarantee the satisfaction of constraints, while also assessing performance within a prediction horizon. By repeatedly solving the online constrained optimization problems, we not only generate an optimal decision sequence for overtaking safely and efficiently but also enhance the adaptability and robustness. This adaptability allows the system to respond effectively to potential changes and unexpected events. Finally, the performance of the proposed MPC framework is demonstrated via simulations of four driving scenarios, which shows that it can handle multiple behaviours. This paper investigates high‐level decision making for autonomous overtaking under two‐way roads subject to oncoming vehicles, one of the most challenging manoeuvres in driving. To accomplish overtaking tasks safely and quickly, a high‐level decision‐making framework is proposed by integrating model predictive control (MPC) and switching control approaches. The performance of the proposed MPC framework is demonstrated via simulations of four driving scenarios, which show that it is able to handle multiple behaviours, including following a leading vehicle, slowdown, stop and overtaking.