Through technological and algorithmic developments, the goal of autonomous driving in private transport has become tangible in recent years. Production vehicles are already equipped with assistance systems that enable autonomous driving in certain situations or that support the driver in intelligent ways. These developments are the result of an interaction of different information systems. Recent developments in the field of machine learning as well as developments in sensor technology contribute to this technological progress. Autonomous vehicles come with an arsenal of sensors that range from LiDAR scanners and optical cameras to radar and ultrasound systems. The information systems relevant to autonomous driving are however not only deployed in the vehicle itself, but also in data centers that are concerned with preprocessing and verification of data as well as training of AI systems. In this talk, the information systems and algorithms relevant to autonomous driving as well as open research questions related to this topic are discussed.