Shared Control Driver Assistance System Based on Driving Intention and Situation Assessment
This paper presents a shared control driver assistance system based on the driving intention identification and situation assessment to avoid obstacles. A constrained linear-time-varying model predictive controller is designed to follow the obstacle-avoidance path, which is obtained by the artificia...
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Published in | IEEE transactions on industrial informatics Vol. 14; no. 11; pp. 4982 - 4994 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Piscataway
IEEE
01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
ISSN | 1551-3203 1941-0050 |
DOI | 10.1109/TII.2018.2865105 |
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Abstract | This paper presents a shared control driver assistance system based on the driving intention identification and situation assessment to avoid obstacles. A constrained linear-time-varying model predictive controller is designed to follow the obstacle-avoidance path, which is obtained by the artificial potential method in real time. A human driver's driving intention and the desired maneuver are recognized by the inductive multilabel classification with an unlabeled data approach that is trained based on the lateral offset and lateral velocity to the road center line. In addition, the situation assessment of the collision risk is represented by the time to collision and the performance evaluation is designed according to lateral deviation. All of them are employed for the design of the shared control fuzzy controller. The cooperative coefficient, denoting the control authority between the controller and a human driver, is determined by three fuzzy controllers in different conditions, which are the consistent, the advanced inconsistent, and the lagged inconsistent fuzzy controller, respectively. More importantly, there are two scenarios studies provided to verify the proposed system. The results prove that the shared control driver assistance system can successfully help drivers to avoid obstacles and obtains great vehicle stability performance in different scenarios. |
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AbstractList | This paper presents a shared control driver assistance system based on the driving intention identification and situation assessment to avoid obstacles. A constrained linear-time-varying model predictive controller is designed to follow the obstacle-avoidance path, which is obtained by the artificial potential method in real time. A human driver's driving intention and the desired maneuver are recognized by the inductive multilabel classification with an unlabeled data approach that is trained based on the lateral offset and lateral velocity to the road center line. In addition, the situation assessment of the collision risk is represented by the time to collision and the performance evaluation is designed according to lateral deviation. All of them are employed for the design of the shared control fuzzy controller. The cooperative coefficient, denoting the control authority between the controller and a human driver, is determined by three fuzzy controllers in different conditions, which are the consistent, the advanced inconsistent, and the lagged inconsistent fuzzy controller, respectively. More importantly, there are two scenarios studies provided to verify the proposed system. The results prove that the shared control driver assistance system can successfully help drivers to avoid obstacles and obtains great vehicle stability performance in different scenarios. |
Author | Huang, Yanjun Song, Xiaolin Cao, Haotian Wang, Jianqiang Li, Mingjun Huang, Zhi |
Author_xml | – sequence: 1 givenname: Mingjun orcidid: 0000-0001-6445-3912 surname: Li fullname: Li, Mingjun email: mingjunl@hnu.edu.cn organization: State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China – sequence: 2 givenname: Haotian orcidid: 0000-0001-5905-4116 surname: Cao fullname: Cao, Haotian email: derrick6925@gmail.com organization: State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China – sequence: 3 givenname: Xiaolin orcidid: 0000-0003-4625-2687 surname: Song fullname: Song, Xiaolin email: jqysxl@hnu.edu.cn organization: State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China – sequence: 4 givenname: Yanjun orcidid: 0000-0003-3133-8031 surname: Huang fullname: Huang, Yanjun email: huangyanjun404@gmail.com organization: Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, Canada – sequence: 5 givenname: Jianqiang orcidid: 0000-0003-4363-6108 surname: Wang fullname: Wang, Jianqiang email: wjqlws@tsinghua.edu.cn organization: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China – sequence: 6 givenname: Zhi surname: Huang fullname: Huang, Zhi email: huangzhi@hnu.edu.cn organization: State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China |
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SubjectTerms | Automobile driving Control systems Control systems design Cooperative coefficient Cooperative control driving intention Force Fuzzy control Informatics model predictive control (MPC) Obstacle avoidance Performance evaluation Predictive control Safety shared control situation assessment Tires Vehicles Wheels |
Title | Shared Control Driver Assistance System Based on Driving Intention and Situation Assessment |
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