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

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.
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Submitted on : Thursday, April 21, 2022 - 11:10:54 AM
Last modification on : Monday, June 27, 2022 - 9:01:27 AM
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Tran Anh-Tu Nguyen, Jagat Jyoti Rath, Chen Lv, Thierry-Marie Guerra, Jimmy Lauber. Human-Machine Shared Driving Control for Semi-Autonomous Vehicles Using Level of Cooperativeness. Sensors, MDPI, 2021, 21 (14), pp.4647. ⟨10.3390/s21144647⟩. ⟨hal-03426491⟩



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