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International audience; Understanding a driver's behavior in a steering task is essential to the development of haptic guidance systems. This paper aims to predict driver torque control, especially when haptic guidance is part of haptic feedback. A new cybernetic driver model with an improved neuromuscular system is proposed and identified. It is assumed that the driver converts a target steering-wheel angle into torque by both indirect and direct control. Indirect control refers to the adaptation of the parameters of an internal model of steering compliance as perceived by the driver. Direct control accounts for the driver's corrective action through direct haptic feedback. The parameters of the model were identified with data collected from experiments conducted with a driving simulator. The results of identification were satisfactory and led to good representation of the driver's action, with or without haptic guidance. The model accurately predicted driver torque output. It can be used to study driver adaptation to haptic guidance systems.

International audience; This paper presents a methodology for the systematic synthesis of haptic shared control (HSC) of a car. This HSC design is based on a two-part architecture. The first part is a trajectory generator that provides a reference trajectory to the second part, which is a static output feedback. In this paper, the haptic shared control is used as an lane keeping assist system (LKA); hence, the reference trajectory is chosen to fulfill this function. The main contribution of this article is related to the combination of the H2/H∞ feedback synthesis. This, involves an H2 criterion quantifying the sharing level and quality as an objective function, and H2/H∞ constraints for lane-keeping performance, driver comfort and robustness. The control design relies on a driver cybernetic model, which decreases conflicts between the assistance and the driver. A systematic method to tune criterion and constraints is described, enabling the attainment of desired lane-following and shared-control performance. The proposed methodology facilitates the design of lateral assistance, ensuring stability and guaranteed performance regardless of the prescribed level of sharing between the actions of the driver and the automaton. The shared control between human driver and automation for the lane keeping task over the Satory test track with the sharing level adaptation is then shown for the validation of the proposed architecture. This work introduces perspectives on smooth transitioning between manual and autonomous driving modes.

International audience; Although the benefits of haptic shared control of the steering wheel have been repeatedly demonstrated, longitudinal studies of how drivers adapt to this kind of system are still lacking. The present study addressed this question by comparing two groups of participants in a driving simulator for an extended time period; one group drove with a shared control system and the other drove without. After the practice, all participants drove a final trial with shared control during which a failure of the system occurred. The results show that the evolution of driving performance and the way in which drivers monitored their performance was similar for the two groups. This suggests that the drivers quickly updated their internal model of the steering system dynamics at the sensorimotor level, without further behavioural adaptation afterwards. However, it appears that the internal model was consolidated with repeated use of the system, which translated as a difficulty to compensate for the system's failure. In addition, it appears that drivers did not attempt to maintain a level of task difficulty when steering was facilitated.