TY  - JOUR
PY  - 2019//
TI  - Optimal control of brakes and steering for autonomous collision avoidance using modified Hamiltonian algorithm
JO  - Vehicle system dynamics
A1  - Gao, Yangyan
A1  - Gordon, Timothy
A1  - Lidberg, Mathias
SP  - 1224
EP  - 1240
VL  - 57
IS  - 8
N2  - 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>
LA  - en
SN  - 0042-3114
UR  - http://dx.doi.org/10.1080/00423114.2018.1563706
ID  - ref1
ER  -