At the Institute of Automotive Engineering (FZD) at TU Darmstadt, we are developing model-based approaches for the holistic description of Automated Driving Systems (ADS) as part of the DFG research project MiRoVA. These are intended to be capable of representing any ADS (Automated Driving System) on a holistic level. This includes the integration of the environment in the form of the Operational Design Domain (ODD), as well as the human-machine interface (HMI) across various designs and levels of automation.

Im Rahmen des Projekts DaCCCar wird am Fachgebiet Fahrzeugtechnik (FZD) an der Entwicklung von langlebigen Fahrzeugkonzepten geforscht. Kunden entscheiden, wann ein Fahrzeug ausgetauscht werden soll. Die fahrzeugbezogenen Faktoren, die auf die Entscheidung einwirken, sollen in dieser Arbeit durch Interviews identifiziert und Komponenten nach ihrer Bedeutung klassifiziert werden.

Research on the topic of perception sensor simulation development and validation in ADAS/automated driving is being conducted at the Institute of Automotive Engineering Darmstadt (FZD). To this end, this thesis aims to develop a method that can be used to systematically derive test scenarios for the development and validation of lidar and radar sensor simulations.

An accurate collection an interpretation of the data plays a central role for the development of driving assistance systems. HD-Maps provide detailed information about the road infrastructure, traffic rules and geometric properties. In order to evaluate and train driving functions, a ground truth is necessary to verify the algorithms.