Vehicle platooning is addressed in this thesis with the aim of contributing in reducing congestion and pollution in urban areas. The researches here focus on cooperative navigation of a fleet of communicating vehicles and relies on a global control approach : each vehicle is controlled from information shared by the entire fleet, using exact linearization techniques. This manuscript presents two theoretical contributions, introducing two new navigation functionalities, and the third contribution consists in their practical implementation. As a first part, the introduction of a manual navigation mode has been investigated, in which the first vehicle, guided by an operator, defines and broadcasts the path to be followed by platoon members. In that case, the numerical representation of the trajectory must be extended without disturbing the portion previously generated, to ensure that the entire platoon can precisely and smoothly follow the leader track. To meet these requirements, the trajectory is modeled using B-Spline curves and an iterative path creating algorithm has been developed from successive positions collected by the lead vehicle during its motion. A parametric analysis has finally resulted in the design of an optimal trajectory with respect to the fidelity of the path representation and to the robustness regarding the disturbances that could arise during the creation procedure. In a second part, a localization strategy relying on monocular vision has been integrated in platoon control algorithms. The localization approach is based on a learning phase during which a video sequence is used to perform a 3D mapping of the environment. However, such a virtual vision world is slightly distorted with respect to the actual metric one. This affects the performances of the platoon control laws. An analysis of distortion has demonstrated that platooning performances can be recovered, provided if a set of local scale factors attached to the reference trajectory is available. Several strategies have then been designed to estimate online such scale factors, either from an observer relying on odometric data, or from an optimization process based on telemetric data. As before, intensive simulations has been run to evaluate parameter influence and highlight the best configurations to use during experiments. Finally, above mentionned algorithms have been implemented in order to present full-scale demonstrators with up to four vehicles (either CyCab or RobuCab). Particular attention is data temporal consistency : since data are collected asynchronously within the platoon, a NTP has been used to synchronize vehicle clock, so that middleware AROCCAM can stamp vehicle data and manage the control scheduling. Thus, vehicle models can be integrated in order to obtain an accurate estimate of the platoon state at the time the control laws are evaluated.
