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

Abstract : This paper proposes a novel haptic shared control concept between human driver and autonomous controller for lane keeping in semi-autonomous vehicles. Based on the human-machine interaction during lane keeping, the level of cooperativeness for completion of driving task is identified. Using the identified level of cooperativeness along with the driver workload, the level of assistance required is determined based on an inverse U-shaped relationship. Subsequently based on the level of assistance required, a factor is developed to modulate the assistance torque generated by the autonomous controller. For the generation of the assistance torque, a new ℓ∞ linear parameter varying (LPV) control technique is proposed to deal with large variations in the vehicle longitudinal speed and those in the modulation factor. The control architecture works on an integrated driver-in-the-loop model developed by considering vehicle yaw-slip dynamics, steering column, and neuromuscular human driver dynamics. Subsequent closed-loop control performance for dynamic road conditions with varying road curvatures is presented through extensive evaluations
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https://hal-uphf.archives-ouvertes.fr/hal-03697763
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Submitted on : Friday, June 17, 2022 - 11:33:37 AM
Last modification on : Saturday, June 18, 2022 - 4:06:31 AM

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Tran Anh-Tu Nguyen, Jagat Jyoti Rath, Chen Lv, Thierry-Marie Guerra. Human-Machine Shared Control for Semi-Autonomous Vehicles Using Level of Cooperativeness. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Oct 2020, Toronto, Canada. pp.2770-2775, ⟨10.1109/SMC42975.2020.9283244⟩. ⟨hal-03697763⟩

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