2026
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation in Autonomous Driving
RA-L 2026
Generating trajectories from high-level commands is critical for autonomous driving, but prevailing methods suffer from a flaw we term semantic misalignment. By associating long trajectories with a single, static meta-action (e.g., “lane change”), these methods corrupt training data during maneuver