This repository implements a diffusion model approach for autonomous driving motion planning, published at ICLR 2025 as an oral presentation. The method uses denoising diffusion processes to generate vehicle trajectories without heavy reliance on refinement stages, enabling flexible guidance for planning in complex driving scenarios. It includes closed-loop evaluation on the nuPlan dataset and supports imitation learning integration.