DREAMS2021: 2nd Workshop on Dynamic Risk ManagEment for AutonoMous Systems Workshop at EDCC2021 (17th European Dependable Computing Conference) Munich, Germany, September 13, 2021 |
Submission link | https://easychair.org/conferences/?conf=dreams2021 |
Abstract registration deadline | June 21, 2021 |
Submission deadline | June 21, 2021 |
Autonomous systems (AS) have enormous potential and are bound to be a major driver in future economic 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, hardly possible at present 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 context in which AS operate. These characteristics render the base assumptions of established assurance methodologies (and standards) insufficient and make it necessary to investigate new approaches at runtime/operation.
One promising approach for building dependable autonomous systems is to design such systems with the capability to identify, assess, and control risks. Implementing such Dynamic Risk Management (DRM) entails many challenges concerning the necessary self-awareness and context awareness. On the one hand, powerful and thus complex self-awareness and context awareness are necessary to minimize risks, resolve conflicting objectives, and make acceptable trade-off decisions. On the other hand, the complexity of the models hinders the assurance of critical properties and prevents gaining sufficient confidence in DRM. DRM has the potential to not only enable certain types of systems or applications outright, but also to significantly increase the performance of already existing ones. This is due to the fact that by resolving unknowns and dealing with uncertainties at runtime, it will be possible to get rid of worst-case assumptions that are typically detrimental to a system’s performance properties.
The DREAMS workshop intends to explore concepts and techniques for realizing DRM. It invites experts, researchers, and practitioners to give presentations and take part in in-depth discussions about prediction models for risk identification, integration between strategic, tactical, and operational risk management, architectures for dynamic risk management, and Validation&Verification of dynamic risk management.
DREAMS aims at bringing together communities from diverse disciplines, such as safety engineering, runtime adaptation, system reconfiguration, predictive modeling, and control theory, and from different application domains such as automotive, healthcare, manufacturing, agriculture, and critical infrastructures.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. Topics of interest include, but are not limited to:
- DRM concepts and methods (e.g., methods for deriving suitable risk metrics)
- DRM architectures
- Layered DRM approaches combining different scopes (e.g., combining DRM at the trajectory planning level and at the maneuver planning level)
- Collaborative DRM performed by groups of cyber-physical systems
- AI-based DRM and trustworthiness considerations
- DRM classifications and taxonomies
- Case studies
Committees
Program Committee
- Rasmus Adler (Fraunhofer IESE, Germany)
- Daniel Schneider (Fraunhofer IESE, Germany)
- Philipp Schleiß (Fraunhofer IKS, Germany)
- Simon Burton (Fraunhofer IKS, Germany)
- Selma Saidi (TU Dortmund, Germany)
Organizing committee
- Huascar Espinoza (CEA, France)
- Patrik Feth (Sick AG, Germany)
- Ibrahim Habli (Univeristy of York, UK)
- Richard Hawkins (Univeristy of York, UK)
- Ayhan Mehmed (TTTech Auto AG, Austria)
- Fabian Oboril (Intel, Germany)
- Yiannis Papadopoulos (University of Hull, UK)
- Gordon Blair (Lancaster University, UK)
- Ganesh Pai (NASA, KBR, USA)
- Phil Kopman (Carnegie Mellon University, USA)
- Eric Armengaud (Armengaud Innovate GmbH, Austria)
- Roman Gansch (Robert Bosch GmbH, Germany)
- Erwin Schoitsch (AIT Austrian Institute of Technology GmbH, Austria)