Modified hamiltonian algorithm for optimal lane change with application to collision avoidance

Gao, Yangyan and Lidberg, Mathias and Gordon, Timothy (2015) Modified hamiltonian algorithm for optimal lane change with application to collision avoidance. MM Science Journal . pp. 576-584. ISSN 1803-1269

Full content URL: https://doi.org/10.17973/mmsj.2015_03_201508

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Item Type:Article
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Abstract

This paper deals with collision avoidance for road vehicles when operating at the limits of available friction. For
collision avoidance, a typical control approach is to: (a) define a reference geometric path that avoids collision; (b) apply low-level control to perform path following. However, there are a number of limitations in this approach, which are addressed in the current paper. First, it is typically unknown whether a predefined reference path is feasible or over-conservative. Secondly, the control scheme is not well suited to avoiding a moving object, e.g. another vehicle. Further: incorrect choice of reference path
may degrade performance, fast adaptation to friction change is
not easy to implement and the associated low-level control
allocation may be computationally intensive. In this paper we use
the general nonlinear optimal control formulation, include some
simplifying assumptions and base optimal control on the
minimization of an underlying Hamiltonian function. A particle
model is used to define an initial reference in the form of a
desired global mass-center acceleration vector. Beyond that, yaw
moment is taken into account for the purpose of enhancing the
stability of the vehicle. The Hamiltonian function is adapted as a
linear function of tyre forces and can be minimized locally for
individual wheels; this significantly reduces computational
workload compared to the conventional approach of forcemoment
allocation. Several combinations of actuators are studied
to show the general applicability of the control algorithm based
on a linear Hamiltonian function. The method has the potential
to be used in future vehicle control systems across a wide range of
safety applications and hence improve overall vehicle agility and
improve safety.

Keywords:Collision avoidance, vehicle control, active safety, vehicle dynamics, intelligent vehicle, optimal control.
Subjects:H Engineering > H140 Mechanics
H Engineering > H330 Automotive Engineering
H Engineering > H230 Transport Engineering
H Engineering > H310 Dynamics
Divisions:College of Science > School of Engineering
ID Code:31232
Deposited On:08 Mar 2018 09:47

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