Optimal control of brakes and steering for autonomous collision avoidance using modified Hamiltonian algorithm. Issue 8 (3rd August 2019)

• Record Type: Journal Article
• Authors: Gao, Yangyan; Gordon, Timothy; Lidberg, Mathias
• Is Part Of: Vehicle system dynamics. Volume 57:Issue 8(2019)
• Page Start: 1224
• Page End: 1240
• Publication Date: 2019-08-03
• Subjects: Vehicle dynamics -- vehicle control -- collision avoidance -- active safety -- stability control; Motor vehicles -- Dynamics -- Periodicals; Electronic journals; 629.231
• DOI: 10.1080/00423114.2018.1563706
• Languages: English
• ISSNs: 0042-3114

Abstract

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.