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The work described in this paper is part of a larger research program named Partage whose goal is to appropriately share lateral control between the driver and an electronic copilot or assistance. The present study is looking for a cybernetic model of a driver steering road vehicle, which makes the sensorimotor dynamics explicit. The proposed model takes into account both visual and kinesthetic perception, and includes compensatory and anticipatory processes. As such, it extends previous works. Starting from simulated car trajectories, the unknown parameters of the model are identified using the grey box identification concept. The driver-vehicle system is then analyzed with respect to the parameter sensitivity.

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International audienceNarrow Tilting Vehicles (NTVs) are the convergence of a car and a motorcycle. They are expected to be the new generation of city cars considering their practical dimensions and lower energy consumption. However, due to their height to breadth ratio, in order to maintain lateral stability, NTVs should tilt when cornering. Unlike the motorcycle, where the driver tilts the vehicle himself, the tilting of an NTV should be automatic. Two tilting systems are available; Direct and Steering Tilt Control, the combined action of these two systems being certainly the key to improve considerably NTV dynamic performances. In this paper, multivariable control tools (H2 methodology) are used to design, in a systematic way, lateral assistance controllers driving DTC, STC or both DTC/STC systems. A three degrees of freedom model of the vehicle is used, as well as a model of the steering signal, leading to a two degrees of freedom low order controller with an efficient feedforward anticipative part. Taking advantage of all the available measurements on NTVs, the lateral acceleration is directly regulated. Finally, a gain-scheduling solution is provided to make the DTC, STC, and DTC/STC controllers robust to longitudinal speed variations

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