The research group Modeling and Analysis in Mobility Software Engineering deals with applied and theoretical methods in the field of autonomous driving. The central research question is: What requirements should an autonomous vehicle fulfill before it is allowed to share the roads of this world with us humans and how can these requirements be ensured? To answer this research question, three basic pillars are pursued in the research. The first research pillar is about the formal specification of driving maneuvers, with which the maneuvers become machine understandable and analyzable. Here, two essential aspects of the maneuvers have to be mapped: Spatial and temporal aspects. Spatial aspects contain, for example, that one vehicle is in front of another, or that an intersection is ahead. Temporal aspects contain, for example, that actions happen sequentially (e.g., blinking before changing lanes), or take a certain amount of time. In this approach, spatial traffic logic and analysis techniques for real-time automata, among others, are used to demonstrate safety, reliability, and other desirable properties of driving maneuvers.

In the next research pillar, the question is raised: What should traffic rules for autonomous vehicles look like? It quickly becomes clear that sets of rules for humans, such as the German Road Traffic Regulations (StVO), cannot be adopted "1 to 1." Natural language is imprecise and many rules require common sense, which cannot be directly transferred to autonomous systems. In this focus area, work is being done on a digital highway code for autonomous vehicles, which contains adapted traffic rules. For such a code, in addition to the machine-readable formulation, the prioritization of traffic rules in exceptional cases, as well as legal and ethical issues, must be considered. The last research pillar aims at the explainability and understandability of complex systems. In times of increasing complexity of autonomous systems, the self-explainability of decisions made by these machines becomes even more important in order to strengthen user trust in the systems, but also to be able to comprehend and verify decisions. For this purpose, methods are being developed with which explanations can be extracted automatically from technical system models. In teaching, these topics will be addressed by a planned lecture on "Timed Systems", as well as in planned practical courses, seminars and topics for theses.