Dr.-Ing.

Schneider, Daniel

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  • Publication
    Towards safety-awareness and dynamic safety management
    ( 2018)
    Trapp, Mario
    ;
    Weiß, Gereon
    ;
    Schneider, Daniel
    Future safety-critical systems will be highly automated or even autonomous and they will dynamically cooperate with other systems as part of a comprehensive ecosystem. This together with increasing utilization of artificial intelligence introduces uncertainties on different levels, which detriment the application of established safety engineering methods and standards. These uncertainties might be tackled by making systems safety-aware and enabling them to manage themselves accordingly. This paper introduces a corresponding conceptual dynamic safety management framework incorporating monitoring facilities and runtime safety-models to create safety-awareness. Based on this, planning and execution of safe system optimizations can be carried out by means of self-adaptation. We illustrate our approach by applying it for the dynamic safety assurance of a single car.
  • Publication
    A Context-Aware, Confidence-Disclosing and Fail-Operational Dynamic Risk Assessment Architecture
    ( 2018)
    Feth, Patrik
    ;
    Adler, Rasmus
    ;
    Schneider, Daniel
    Future automotive systems will be highly automated and they will cooperate to optimize important system qualities and performance. Established safety assurance approaches and standards have been designed with manually controlled stand-alone systems in mind and are thus not fit to ensure safety of this next generation of systems. We argue that, given frequent dynamic changes and unknown contexts, systems need to be enabled to dynamically assess and manage their risks. In doing so, systems become resilient from a safety perspective, i.e. they are able to maintain a state of acceptable risk even when facing changes. This work presents a Dynamic Risk Assessment architecture that implements the concepts of context-awareness, confidence-disclosure and fail-operational. In particular, we demonstrate the utilization of these concepts for the calculation of automotive collision risk metrics, which are at the heart of our architecture.