Thanks to the DARPA Urban Challenge in 2007, the launch a few years later of the Google Car project, the recent multiple announcements of the Automotive Industry, and the wide dissemination by the media of nice interviews and videos, the concept of Autonomous Driving seems to progressively become a reality for the next decades. The objective of this talk is to give a brief analysis of the state of the art, before focusing on one of the current brake on the deployment of such a technology: the lack of robustness and of efficiency of current Embedded Perception and Decision-making systems. New technologies and trends will be presented for addressing these issues. It will be shown that Bayesian approaches are mandatory for developing such technologies and for obtaining the required robustness in presence of uncertainty and complex dynamic situations. The talk will be illustrated by some interesting results obtained at Inria in the scope of several collaborative projects involving Toyota, Renault, CEA-LETI, or the French IRT (Technological Research Institute) Nanoelec.