Title: An efficient model-free setting for longitudinal and lateral vehicle control. Validation through the interconnected pro-SiVIC/RTMaps prototyping platform,
Abstract: In this paper, the problem of tracking desired longitudinal and lateral
motions for a vehicle is addressed. Let us point out that a "good" modeling is
often quite difficult or even impossible to obtain. It is due for example to
parametric uncertainties, for the vehicle mass, inertia or for the interaction
forces between the wheels and the road pavement. To overcome this type of
difficulties, we consider a model-free control approach leading to
"intelligent" controllers. The longitudinal and the lateral motions, on one
hand, and the driving/braking torques and the steering wheel angle, on the
other hand, are respectively the output and the input variables. An important
part of this work is dedicated to present simulation results with actual data.
Actual data, used in Matlab as reference trajectories, have been previously
recorded with an instrumented Peugeot 406 experimental car. The simulation
results show the efficiency of our approach. Some comparisons with a nonlinear
flatness-based control in one hand, and with a classical PID control in another
hand confirm this analysis. Other virtual data have been generated through the
interconnected platform SiVIC/RTMaps, which is a virtual simulation platform
for prototyping and validation of advanced driving assistance systems.