End-to-End Autonomous Driving: Motion Planning Under Distribution Shifts

Overview

Combines ongoing work on residual-reinforcement-learning fine-tuning of motion planners in CARLA with experiments using diffusion likelihoods for trajectory OOD detection. Discusses training/test scenario separation and evaluates anomalous trajectories with the MAAD dataset.