Vehicle optimal road departure prevention via model predictive control

Yuan, Hongliang, Gao, Yangyan and Gordon, Timothy J. (2017) Vehicle optimal road departure prevention via model predictive control. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 231 (7). pp. 952-962. ISSN 0954-4070

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Vehicle optimal road departure prevention via model predictive contro
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Item Type:Article
Item Status:Live Archive


This article addresses the problem of road departure prevention using integrated brake control. The scenario
considered is when a high speed vehicle leaves the highway on a curve and enters the shoulder or another lane,
due to excessive speed, or where the friction of the road drops due to adverse weather conditions. In such a scenario,
the vehicle speed is too high for the available tyre-road friction and road departure is inevitable; however, its effect can
be minimized with an optimal braking strategy. To achieve online implementation, the task is formulated as a receding
horizon optimization problem and solved in a linear model predictive control (MPC) framework. In this formulation, a
nonlinear tire model is adopted in order to work properly at the friction limits. The optimization results are close to
those obtained previously using a particle model optimization, PPR, coupled to a control algorithm, MHA, specifically
designed to operate at the vehicle friction limits. This shows the MPC formulation may equally be effective for vehicle
control at the friction limits. The major difference here, compared to the earlier PPR/MHA control formulation, is that
the proposed MPC strategy directly generates an optimal brake sequence, while PPR provides an optimal reference
first, then MHA responds to the reference to give closed-loop actuator control. The presented MPC approach has the
potential to be used in future

Keywords:Vehicle dynamics, model predictive control, vehicle safety system, vehicle braking control, passenger vehicles
Subjects:H Engineering > H330 Automotive Engineering
Divisions:College of Science > School of Engineering
ID Code:26728
Deposited On:16 Mar 2017 09:52

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