VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning
arXiv:2402.13243v2 Announce Type: replace-cross
Abstract: Learning a human-like driving policy from large-scale driving demonstrations is promising, but the uncertainty and non-deterministic nature of planning make it challenging. Existing learning-ba…