1 citations · 2 across the 3 of their papers we have counts for
5 papers
When and How Severely: Scenario-Specific Safety Envelopes for Driving VLAs
Abhinaw Priyadershi, Jelena Frtunikj
Safety certification of Vision-Language-Action (VLA) driving planners under ISO 21448 (SOTIF) rests on an Operational Design Domain (ODD) specification that answers two complementa…
Output Type Before Quality: A Standards-Derived XAI Admissibility Rubric for Autonomous-Driving Safety
Abhinaw Priyadershi, Mandar Pitale, Jelena Frtunikj +1
Safety standards for ML-based autonomous driving specify the kind of evidence an assurance case must contain (directed cause-and-effect chains, quantified interventional effects, n…
Lost in Fog: Sensor Perturbations Expose Reasoning Fragility in Driving VLAs
Abhinaw Priyadershi, Jelena Frtunikj
Interpretable autonomous driving planners depend not only on generating explanations, but also on those explanations remaining reliable under real-world sensor degradation. In this…
HySafe-AI: Hybrid Safety Architectural Analysis Framework for AI Systems: A Case Study
Mandar Pitale, Jelena Frtunikj, Abhinaw Priyadershi +2
AI has become integral to safety-critical areas like autonomous driving systems (ADS) and robotics. The architecture of recent autonomous systems are trending toward end-to-end (E2…
How much data do you need? Part 2: Predicting DL class specific training dataset sizes
Thomas Mühlenstädt, Jelena Frtunikj
This paper targets the question of predicting machine learning classification model performance, when taking into account the number of training examples per class and not just the…