Optimal control of brakes and steering for autonomous collision avoidance using modified Hamiltonian algorithm

Gao, Yangyan and Gordon, Timothy and Lidberg, Matthias (2019) Optimal control of brakes and steering for autonomous collision avoidance using modified Hamiltonian algorithm. Vehicle System Dynamics . ISSN 0042-3114

Full content URL: https://doi.org/10.1080/00423114.2018.1563706

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Optimal control of brakes and steering for autonomous collision avoidance using modified Hamiltonian algorithm
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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.

Keywords:Vehicle dynamics, vehicle control, collision avoidance, active safety, stability control
Subjects:H Engineering > H660 Control Systems
H Engineering > H300 Mechanical Engineering
H Engineering > H331 Road Vehicle Engineering
Divisions:College of Science > School of Engineering
ID Code:34912
Deposited On:05 Mar 2019 16:38

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