Literature DB >> 34300387

Human-Machine Shared Driving Control for Semi-Autonomous Vehicles Using Level of Cooperativeness.

Anh-Tu Nguyen1, Jagat Jyoti Rath2, Chen Lv3, Thierry-Marie Guerra1, Jimmy Lauber1.   

Abstract

This paper proposes a new haptic shared control concept between the human driver and the automation for lane keeping in semi-autonomous vehicles. Based on the principle of human-machine interaction during lane keeping, the level of cooperativeness for completion of driving task is introduced. Using the proposed human-machine cooperative status along with the driver workload, the required level of haptic authority is determined according to the driver's performance characteristics. Then, a time-varying assistance factor is developed to modulate the assistance torque, which is designed from an integrated driver-in-the-loop vehicle model taking into account the yaw-slip dynamics, the steering dynamics, and the human driver dynamics. To deal with the time-varying nature of both the assistance factor and the vehicle speed involved in the driver-in-the-loop vehicle model, a new ℓ∞ linear parameter varying control technique is proposed. The predefined specifications of the driver-vehicle system are guaranteed using Lyapunov stability theory. The proposed haptic shared control method is validated under various driving tests conducted with high-fidelity simulations. Extensive performance evaluations are performed to highlight the effectiveness of the new method in terms of driver-automation conflict management.

Entities:  

Keywords:  human-machine shared control; lane keeping assistance; polytopic LPV control

Year:  2021        PMID: 34300387     DOI: 10.3390/s21144647

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  An Integrated Framework for Multi-State Driver Monitoring Using Heterogeneous Loss and Attention-Based Feature Decoupling.

Authors:  Zhongxu Hu; Yiran Zhang; Yang Xing; Qinghua Li; Chen Lv
Journal:  Sensors (Basel)       Date:  2022-09-29       Impact factor: 3.847

  1 in total

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