A standards-derived rubric shows causal XAI is required for hazard identification, incident investigation, and data management in ADS safety cases, while other methods suffice elsewhere.
Explainable AI for safe and trustworthy autonomous driving: A systematic review
2 Pith papers cite this work. Polarity classification is still indexing.
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The paper introduces a unified algebraic framework that applies the Pearson Correlation Coefficient to Time Surface, Event Frame, and Voxel Grid representations of event camera streams to yield task-agnostic integrity metrics.
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Output Type Before Quality: A Standards-Derived XAI Admissibility Rubric for Autonomous-Driving Safety
A standards-derived rubric shows causal XAI is required for hazard identification, incident investigation, and data management in ADS safety cases, while other methods suffice elsewhere.