Vehicle optimal road departure prevention via model predictive control. (June 2017)
- Record Type:
- Journal Article
- Title:
- Vehicle optimal road departure prevention via model predictive control. (June 2017)
- Main Title:
- Vehicle optimal road departure prevention via model predictive control
- Authors:
- Yuan, Hongliang
Gao, Yangyan
Gordon, Timothy J - Abstract:
- 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, owing to excessive speed or a reduction in the friction of the road 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 tyre 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, parabolic path reference (PPR), coupled to a control algorithm, the modified Hamiltonian algorithm (MHA), specifically designed to operate at the vehicle friction limits. This shows that the MPC formulation may be equally effective for vehicle control at the friction limits. The major difference here, compared with 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 for use inThis 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, owing to excessive speed or a reduction in the friction of the road 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 tyre 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, parabolic path reference (PPR), coupled to a control algorithm, the modified Hamiltonian algorithm (MHA), specifically designed to operate at the vehicle friction limits. This shows that the MPC formulation may be equally effective for vehicle control at the friction limits. The major difference here, compared with 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 for use in future vehicle systems as part of the overall active safety control to improve overall vehicle agility and safety. … (more)
- Is Part Of:
- Proceedings of the Institution of Mechanical Engineers. Volume 231:Number 7(2017:Jul.)
- Journal:
- Proceedings of the Institution of Mechanical Engineers
- Issue:
- Volume 231:Number 7(2017:Jul.)
- Issue Display:
- Volume 231, Issue 7 (2017)
- Year:
- 2017
- Volume:
- 231
- Issue:
- 7
- Issue Sort Value:
- 2017-0231-0007-0000
- Page Start:
- 952
- Page End:
- 962
- Publication Date:
- 2017-06
- Subjects:
- Vehicle dynamics -- model predictive control -- vehicle safety system -- vehicle braking control -- passenger vehicles
Mechanical engineering -- Congresses
Transportation engineering -- Congresses
629.2 - Journal URLs:
- http://pid.sagepub.com/ ↗
http://www.uk.sagepub.com/home.nav ↗
http://journals.pepublishing.com/content/119783 ↗ - DOI:
- 10.1177/0954407017701286 ↗
- Languages:
- English
- ISSNs:
- 0954-4070
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7687.xml