From Level Four to Five: Getting rid of the Safety Driver with Diagnostics in Autonomous Driving

During the past years autonomous driving evolved from only being a major topic in scientific research, all the way to practical and commercial applications like on-demand public transportation. Together with this evolution new use cases arose, making reliability and robustness of the complete system more important than ever. Many different stakeholders during development and operation as well as independent certification and admission authorities pose additional challenges. By providing and capturing additional information about the running system, independent of the main driving task (e.g. by components self tests or performance observations) the overall robustness, reliability and safety of the vehicle is increased. This article captures the issues of autonomous driving in modern-day real-life use cases and defines what a diagnostic system needs to look like to tackel these challenges. Furthermore the authors provide a concept for diagnostics in the heterogenous software landscape of component based autonomous driving architectures regarding their special complexities and difficulties.