Autonomous Driving, here we go?

In addition to this increase in comfort, the major benefits of vehicle automation include resource-saving driving through optimized traffic flows and greater safety for all road users. According to the classification of the SAE (Society of Automotive Engineers) and the VDA (German Association of the Automotive Industry), this can be divided into 5 levels. Today's state of the art includes vehicles with automation levels 2 to 3. The last level is referred to as "autonomous driving". Here, the vehicle is completely guided by the system and performs all the necessary tasks automatically in every situation.

In addition to this increase in comfort, the major advantages of vehicle automation include resource-saving driving thanks to optimized traffic flows and greater safety for all road users. According to the classification of the SAE (Society of Automotive Engineers) and the VDA (German Association of the Automotive Industry), this can be divided into 5 levels. Today's state of the art includes vehicles with automation levels 2 to 3. The last level is referred to as "autonomous driving". Here, the vehicle is completely guided by the system and performs all the necessary tasks automatically in every situation.

In the application cluster, the developments and innovations from the current state of the art to autonomous driving are to be scientifically accelerated. Artificial intelligence is considered a promising method to make the complexity of autonomous mobility manageable, due to the infinite variety of variants and the underlying non-linear relationships in traffic. AI can be used as a pervasive technology in the perception, planning and control of traffic flows (macroscopic) and individual movements of mobility carriers (microscopic), but also for data-based services. Through AI-supported vehicle automation, vehicle manufacturers, suppliers and SMEs are to expand their leading international position. Innovations required for this are to be developed and tested in the Bavarian AI network for mobility.

Professors in Autnomous Driving

Prof. Dr. rer. nat. Lenz Belzner
Software Methodology for Autonomous Mobility Systems
Prof. Dr.-Ing. Michael Botsch
Vehicle Safety and Signal Processing
Prof. Dr. rer. nat. Stefan Kugele
Model-based Systems Engineering und Software Engineering
Prof. Dr.-Ing. Richard Membarth
System on a Chip and AI for Edge Computing