@article{ref1,
title="Optimal control of brakes and steering for autonomous collision avoidance using modified Hamiltonian algorithm",
journal="Vehicle system dynamics",
year="2019",
author="Gao, Yangyan and Gordon, Timothy and Lidberg, Mathias",
volume="57",
number="8",
pages="1224-1240",
abstract="This paper considers the problem of collision avoidance for road vehicles, operating at the limits of friction. A two-level modelling and control methodology is proposed, with the upper level using a friction-limited particle model for motion planning, and the lower level using a nonlinear 3DOF model for optimal control allocation. Motion planning adopts a two-phase approach: the first phase is to avoid the obstacle, the second is to recover lane keeping with minimal additional lateral deviation. This methodology differs from the more standard approach of path-planning/path-following, as there is no explicit path reference used; the control reference is a target acceleration vector which simultaneously induces changes in direction and speed. The lower level control distributes vehicle targets to the brake and steer actuators via a new and efficient method, the Modified Hamiltonian Algorithm (MHA). MHA balances CG acceleration targets with yaw moment tracking to preserve lateral stability. A nonlinear 7DOF two-track vehicle model confirms the overall validity of this novel methodology for collision avoidance.<p /> <p>Language: en</p>",
language="en",
issn="0042-3114",
doi="10.1080/00423114.2018.1563706",
url="http://dx.doi.org/10.1080/00423114.2018.1563706"
}