@inproceedings{4a5f8838056143e09c6eb81c2ea2ea54,
title = "Design and evaluation of path following controller based on MPC for autonomous vehicle",
abstract = "This paper proposes a model predictive control (MPC) for autonomous vehicle path following control. To solve the control problem, a nonlinear path following model is used, which includes 2 degree-of-freedom single track vehicle dynamics model and path following error model. The control problem is to control vehicle to run on the reference path with the heading angle along the road orientation angle. Then, a controller based on MPC method is designed, and a C-based algorithm is implemented to solve the nonlinear optimization problem in real-time. The proposed control system is tested in a hardware-in-the-loop simulation platform and the robustness is tested by adding noise to lateral vehicle speed and modifying model parameters. It is testified that the control performance is satisfied in different situations.",
keywords = "Autonomous vehicle, hardware-in-the-loop simulation, model predictive control, path following",
author = "Hongliang Zhou and Levent Guvenc and Zhiyuan Liu",
note = "Publisher Copyright: {\textcopyright} 2017 Technical Committee on Control Theory, CAA.; 36th Chinese Control Conference, CCC 2017 ; Conference date: 26-07-2017 Through 28-07-2017",
year = "2017",
month = sep,
day = "7",
doi = "10.23919/ChiCC.2017.8028942",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "9934--9939",
editor = "Tao Liu and Qianchuan Zhao",
booktitle = "Proceedings of the 36th Chinese Control Conference, CCC 2017",
address = "美国",
}