Autonomous systems have enormous potential and they are bound to be a major driver in future economical and societal transformations. Their key trait is that they pursue and achieve their more or less explicitly defined goals independently and without human guidance or intervention. In contexts where safety, or other critical properties, need to be guaranteed it is, however, presently hardly possible to exploit autonomous systems to their full potential. Unknowns and uncertainties are induced due to high complexity of the autonomous behaviors, the utilized technology and the volatile and highly complex system contexts. These characteristics render the base assumptions of established assurance methodologies (and standards) void, hence new approaches need to be investigated. One general approach to deal with such unknowns and uncertainties is to shift parts of the development time assurance activities into runtime when all required information can be resolved.

Giving systems runtime assurance capabilities means empowering them to monitor their environments (i.e. other collaborating systems as well as the physical environment), analyze and reason about implications regarding key safety requirements, and, execute control actions to ensure adherence to these requirements at any time – thus conducting Dynamic Risk Management (DRM). DRM has the potential to not only outright enable certain types of systems or applications, but also to significantly increase the performance of already existing ones. This is due to the fact that by resolving unknowns and uncertainties at runtime it will be possible to get rid of worst case assumptions that typically detriment the systems performance properties. The DREAMS workshop intends to explore concepts and techniques for realizing DRM. It invites experts, researchers, and practitioners for presentations and in-depth discussions about prediction models for risk identification, integration between strategic, tactical and operational risk management, architectures for dynamic risk management, and V&V of dynamic risk management.

DREAMS aims at bringing together communities from diverse disciplines, such as safety engineering, runtime adaptation, predictive modelling, control theory, and from different application domains such as automotive, healthcare, manufacturing, agriculture and critical infrastructures.

Topics of interest include but are not limited to:
DRM concepts and methods (e.g., methods to derive suitable risk metrics)
DRM architectures
Layered DRM approaches combining different scopes (e.g., combining DRM at trajectory planning level and at maneuver planning)
Collaborative DRM performed by groups of cyber-physical systems
AI-based DRM and trustworthiness considerations
DRM classifications and taxonomies
Case studies