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Risk Management Core -- Towards an Explicit Representation of Risk in Automated Driving
While current automotive safety standards provide implicit guidance on how unreasonable risk can be avoided, manufacturers are required to specify risk acceptance criteria for Automated Driving Systems (SAE Level 3 and higher).
Ein Beitrag zur durchgängigen, formalen Verhaltensspezifikation automatisierter Straßenfahrzeuge
With the introduction of the \textit{semantic norm behavior analysis} a method is proposed, which contributes to a traceable mapping of concerns towards the behavior of an automated vehicle in its operational environment to a formal rule system of semantic concepts for considered scenarios.
Phenomenon-Signal Model: Formalisation, Graph and Application
The aim of this paper is to explain the basics, the structure and the application of this method.
Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception
This poses a challenge with respect to the realization of safety-critical perception tasks by means of DDMs.
Integrating Testing and Operation-related Quantitative Evidences in Assurance Cases to Argue Safety of Data-Driven AI/ML Components
Using the proposed argumentation structure might not only increase the integrity of assurance cases but may also allow claims on quantitative targets that would not be justifiable otherwise.
