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In this paper, the problem of tracking desired longitudinal and lateralmotions for a vehicle is addressed. Let us point out that a "good" modeling isoften quite difficult or even impossible to obtain. It is due for example toparametric uncertainties, for the vehicle mass, inertia or for the interactionforces between the wheels and the road pavement. To overcome this type ofdifficulties, we consider a model-free control approach leading to"intelligent" controllers. The longitudinal and the lateral motions, on onehand, and the driving/braking torques and the steering wheel angle, on theother hand, are respectively the output and the input variables. An importantpart of this work is dedicated to present simulation results with actual data.Actual data, used in Matlab as reference trajectories, have been previouslyrecorded with an instrumented Peugeot 406 experimental car. The simulationresults show the efficiency of our approach. Some comparisons with a nonlinearflatness-based control in one hand, and with a classical PID control in anotherhand confirm this analysis. Other virtual data have been generated through theinterconnected platform SiVIC/RTMaps, which is a virtual simulation platformfor prototyping and validation of advanced driving assistance systems.

An efficient model-free setting for longitudinal and lateral vehicle  control. Validation through the interconnected pro-SiVIC/RTMaps prototyping  platform