Learning to Explain While Planning: Rule-Aligned Diffusion Planning for Autonomous Driving

Excerpt

arXiv:2609.39995v1 Announce Type: new Abstract: Diffusion planners exhibit strong capabilities in generating multimodal trajectories. However, existing methods primarily rely on expert demonstrations to fit trajectory distributions, learning statistical correlations among scenes, behaviors, and trajectories without explicitly modeling driving rules. In long-tail scenarios where expert data are scarce, the lack of behaviors to imitate may lead to trajectories that violate safety or compliance req