Mechanistic Interpretability for End-to-End Self-Driving
Mechanistic interpretability to E2E driving is applied by training Sparse Autoencoders on the internal activations of a simple, single-camera end-to-end path planning model, revealing interpretable structure aligned with route intent, vehicle speed, and braking behavior.
Manav Gagvani, Benjamin Namikas, Sivamurugan Velmurugan et al.
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