Shared steering control combined with driving intention for vehicle obstacle avoidance. (September 2019)
- Record Type:
- Journal Article
- Title:
- Shared steering control combined with driving intention for vehicle obstacle avoidance. (September 2019)
- Main Title:
- Shared steering control combined with driving intention for vehicle obstacle avoidance
- Authors:
- Li, Mingjun
Song, Xiaolin
Cao, Haotian
Huang, Zhi - Abstract:
- This paper presents a framework of shared steering control for vehicle obstacle avoidance, which is combined with the driver's driving intention and risk assessment. The driving intention is recognized by a support vector machine model through the steering wheel angle, the relative lateral offset, and lateral velocity to the road center line. The elastic band theory is adopted to plan the obstacle avoidance path, which takes the driving intention and environment information into consideration. A linear model predictive control algorithm based on a bicycle vehicle model is used to realize path following. The risk assessment of current traffic situation is calculated by time to collision and the time required from the starting position of lane changing to the obstacle to collide. The shared steering control strategy is designed by the risk assessment and driving intention, simultaneously, so that the cooperative coefficient and the driving mode would be determined. In order to validate the framework proposed in this paper, the shared steering control system is tested on four obstacle avoidance scenarios, including the static and moving obstacles on a straight road and a curvy road. The results show that the shared steering control system could help the human driver avoid obstacles safely. Besides, both the path and steering wheel angle curve of the shared steering control system are smooth, and the vehicle stability performance also maintains well through a suitable sharedThis paper presents a framework of shared steering control for vehicle obstacle avoidance, which is combined with the driver's driving intention and risk assessment. The driving intention is recognized by a support vector machine model through the steering wheel angle, the relative lateral offset, and lateral velocity to the road center line. The elastic band theory is adopted to plan the obstacle avoidance path, which takes the driving intention and environment information into consideration. A linear model predictive control algorithm based on a bicycle vehicle model is used to realize path following. The risk assessment of current traffic situation is calculated by time to collision and the time required from the starting position of lane changing to the obstacle to collide. The shared steering control strategy is designed by the risk assessment and driving intention, simultaneously, so that the cooperative coefficient and the driving mode would be determined. In order to validate the framework proposed in this paper, the shared steering control system is tested on four obstacle avoidance scenarios, including the static and moving obstacles on a straight road and a curvy road. The results show that the shared steering control system could help the human driver avoid obstacles safely. Besides, both the path and steering wheel angle curve of the shared steering control system are smooth, and the vehicle stability performance also maintains well through a suitable shared strategy. … (more)
- Is Part Of:
- Proceedings of the Institution of Mechanical Engineers. Volume 233:Number 11(2019:Nov.)
- Journal:
- Proceedings of the Institution of Mechanical Engineers
- Issue:
- Volume 233:Number 11(2019:Nov.)
- Issue Display:
- Volume 233, Issue 11 (2019)
- Year:
- 2019
- Volume:
- 233
- Issue:
- 11
- Issue Sort Value:
- 2019-0233-0011-0000
- Page Start:
- 2791
- Page End:
- 2808
- Publication Date:
- 2019-09
- Subjects:
- Shared steering control -- driving intention -- risk assessment -- cooperative coefficient -- obstacle avoidance
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:
- 10.1177/0954407018806147 ↗
- 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:
- 11316.xml