Programmable Systems for Intelligence in Automobiles (PRYSTINE): Technical Progress after Year 2

As originally submitted and published there was an error in this document. The authors subsequently provided the following text: "The article is a co-development of many authors from many organizations. Only the first author affiliation was provided on the article PDF. The following additional author affiliations are noted: Kaspars Ozols (Institute of Electronics and Computer Science, Latvia); Rihards Novickis (Institute of Electronics and Computer Science, Latvia); Aleksandrs Levinskis (Institute of Electronics and Computer Science, Latvia)." The original article PDF remains unchanged.Autonomous driving has the potential to disruptively change the automotive industry as we know it today. For this, fail-operational behavior is essential in the sense, plan, and act stages of the automation chain in order to handle safety-critical situations by its own, which currently is not reached with state-of-the-art approaches.The European ECSEL research project PRYSTINE realizes Fail-operational Urban Surround perceptION (FUSION) based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments. This paper showcases some of the key results (e.g., novel Radar sensors, innovative embedded control and E/E architectures, pioneering sensor fusion approaches, AI controlled vehicle demonstrators) achieved until year 2.Peer reviewe