AI RESEARCH
Towards a Systematic Risk Assessment of Deep Neural Network Limitations in Autonomous Driving Perception
arXiv CS.LG
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ArXi:2604.20895v1 Announce Type: cross Safety and security are essential for the admission and acceptance of automated and autonomous vehicles. Deep neural networks (DNNs) are widely used for perception and further components of the autonomous driving (AD) stack. However, they possess several limitations, including lack of generalization, efficiency, explainability, plausibility, and robustness. These insufficiencies can pose significant risks to autonomous driving systems.