4 papers across 3 sessions
An end-to-end RL-based OARSMT construction method.
A 3DGS-based Reinforcement Learning training paradigm for end-to-end autonomous driving
We propose an end-to-end autonomous driving framework based on a unified diffusion-regression-classification policy, achieving state-of-the-art performance on both the CARLA and NAVSIM benchmarks.
