Lectures

The lecture aims to provide the technical basics of (highly) automated driving.

The topic of automated driving is structured and a general overview is given. This contains the history of automated driving, a current evaluation of its societal aspects, the societal framework within which automated vehicles are developed and used, the legal boundary conditions as well as the economic challenges and potential benefits. The different levels of automation and connectivity of automated vehicles are explained according to different classification schemes. A functional architecture of automated vehicles is introduced.

An introduction into fundamental mathematical and methodological basics focusing on essential principles of optimization, statistics and machine learning form the basis for understanding the technical context of the architecture of automated vehicles and selected functional modules. Subsequently, the topics sensors, perception, environment modeling, prediction, behavior planning, trajectory planning and optimization as well as vehicle control are being covered.

Possible software and hardware architectures of automated vehicles, aspects of human-machine interaction as well as cooperative and connected driving are part of this course.

Finally, key principles of the development process of automated vehicles for a possible deployment on public roads are covered. The safety assurance methodology and the impact assessment of automated vehicles are covered as both aspects are fundamentally different from current processes, which are insufficient for automated vehicles.