@inproceedings{discovery10189766,
           month = {July},
            note = {This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.},
           title = {Game-Theoretic Model Predictive Control for Safety-Assured Autonomous Vehicle Overtaking in Mixed-Autonomy Environment},
            year = {2024},
       booktitle = {Proceedings of the 22nd European Control Conference},
       publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
         journal = {22nd European Control Conference},
          author = {Yu, Sheng and Chen, Boli and Jaimoukha, Imad M and Evangelou, Simos A},
        abstract = {This work proposes a robust control strategy for an autonomous vehicle to overtake safely and comfortably a human-driven vehicle. The proposed scheme designs a collisionavoidance constraint setup that comprehensively coordinates dimension-based and velocity-dependent constraints to fulfil the safety criteria. A three-phase control framework is proposed for the overtaking task, subject to separate collision-avoidance constraints in lane changing, passing, and merging phases. Moreover, the proposed method utilises a Stackelberg game model to interactively involve the human-driven overtaken vehicle behaviours in the online optimisation loop. To further cope with uncertainties caused by the human driver, the optimisation is solved by a robust model predictive controller to guarantee the avoidance of collisions. Numerical case studies verify that the proposed framework is capable of overtaking not only a cooperative human-driven vehicle but also an uncooperative human-driven vehicle with safe and comfortable trajectories.},
             url = {https://ieeexplore.ieee.org/Xplore/home.jsp}
}