SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving

ArXi:2604.01337v1 Announce Type: new While deep learning has significantly advanced accident anticipation, the robustness of these safety-critical systems against real-world perturbations remains a major challenge. We reveal that state-of-the-art models like CRASH, despite their high performance, exhibit significant instability in predictions and latent representations when faced with minor input perturbations, posing serious reliability risks. To address this, we