@inproceedings{f8fc5aec896142ec9ba8746c1f9d7c0b,
title = "Explicit Model Predictive Control for Trajectory Tracking of Autonomous Vehicle",
abstract = "Autonomous vehicle has been attached more and more attention since it is considered as an effective solution to transportation problems. This paper focuses on the trajectory tracking control algorithms for autonomous vehicles. To improve the computational efficiency, a constrained explicit controller with offline optimization and online search is proposed based on the original model predictive control (MPC) algorithm. The joint simulation based on the Simulink and Carsim is designed to evaluate the performance of proposed explicit controller. The results show that compared with the original MPC controller, the explicit controller can significantly reduce optimization time and achieve relatively similar tracking performance.",
keywords = "autonomous vehicle, explicit model predictive control, joint simulation, model predictive control, trajectory tracking",
author = "Xiangkang Lai and Haolong Jiang and Qinyao Liu and Qian Guo and Xuchen Wang",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 China Automation Congress, CAC 2023 ; Conference date: 17-11-2023 Through 19-11-2023",
year = "2023",
doi = "10.1109/CAC59555.2023.10451459",
language = "English",
series = "Proceedings - 2023 China Automation Congress, CAC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5154--5159",
booktitle = "Proceedings - 2023 China Automation Congress, CAC 2023",
}