17 citations · 49 across the 6 of their papers we have counts for
6 papers
Causal Bayesian Networks for Data-driven Safety Analysis of Complex Systems
Roman Gansch, Lina Putze, Tjark Koopmann +2
Ensuring safe operation of safety-critical complex systems interacting with their environment poses significant challenges, particularly when the system's world model relies on mac…
System Theoretic View on Uncertainties
Roman Gansch, Ahmad Adee
The complexity of the operating environment and required technologies for highly automated driving is unprecedented. A different type of threat to safe operation besides the fault-…
Discovery of Perception Performance Limiting Triggering Conditions in Automated Driving
Ahmad Adee, Roman Gansch, Peter Liggesmeyer +2
Highly automated driving (HAD) vehicles are complex systems operating in an open context. Performance limitations originating from sensing and understanding the open context under…
Systematic Modeling Approach for Environmental Perception Limitations in Automated Driving
Ahmad Adee, Roman Gansch, Peter Liggesmeyer
Highly automated driving (HAD) vehicles are complex systems operating in an open context. Complexity of these systems as well as limitations and insufficiencies in sensing and unde…
Grasping Causality for the Explanation of Criticality for Automated Driving
Tjark Koopmann, Christian Neurohr, Lina Putze +3
The verification and validation of automated driving systems at SAE levels 4 and 5 is a multi-faceted challenge for which classical statistical considerations become infeasible. Fo…
Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception
Janek Groß, Rasmus Adler, Michael Kläs +3
Data-driven models (DDM) based on machine learning and other AI techniques play an important role in the perception of increasingly autonomous systems. Due to the merely implicit d…