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TRV-2026-0981Certified recordPeer-reviewed

Explainable deep learning improves human mental models of self-driving cars

Self-driving cars increasingly rely on deep neural networks to achieve human-like driving 1-3 . The opacity of these black-box planners makes it challenging to accurately anticipate when they will fail 4-6 , with potentially catastrophic consequences 7-9 . Although research into interpreting these systems has surged, most of it is confined to simulations or toy setups because of the difficulty of real-world deployment 10,11 , leaving the practical utility of these techniques unknown. Here, we introduce the Conce…

Science · P Space — documented harm · certified 2026-09-04 · v1 · article view · machine-readable

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Explainable deep learning improves human mental models of self-driving cars: The opacity of these black-box planners makes it challenging to accurately anticipate when they will fail 4-6 , with potentially catastrophic consequences 7-9 .

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Truvace Impact Record TRV-2026-0981, v1: “Explainable deep learning improves human mental models of self-driving cars.” Truvace, 2026-09-04. /record/TRV-2026-0981 (accessed at citation time). sha256 e9ea0b99d166c65c…

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