AI RESEARCH
Collision-Aware Vision-Language Learning for End-to-End Driving with Multimodal Infraction Datasets
arXiv CS.AI
•
ArXi:2603.25946v1 Announce Type: cross High infraction rates remain the primary bottleneck for end-to-end (E2E) autonomous driving, as evidenced by the low driving scores on the CARLA Leaderboard. Despite collision-related infractions being the dominant failure mode in closed-loop evaluations, collision-aware representation learning has received limited attention.