ZhengYinan-AIR/Diffusion-Planner

[ICLR 2025 Oral] The official implementation of "Diffusion-Based Planning for Autonomous Driving with Flexible Guidance"

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Diffusion Planner employs a DiT-based architecture that jointly models vehicle trajectories and environmental context as a unified future trajectory generation problem, eliminating heavy reliance on iterative refinement. It achieves ~20Hz real-time inference through fast diffusion sampling and supports flexible guidance mechanisms (e.g., classifier guidance) for controllable planning. The framework is evaluated on nuPlan's closed-loop benchmark and integrates with nuplan-devkit for end-to-end autonomous driving validation.

897 stars. Actively maintained with 1 commit in the last 30 days.

No License No Package No Dependents
Maintenance 16 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 22 / 25

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Stars

897

Forks

132

Language

Python

License

Last pushed

Mar 10, 2026

Commits (30d)

1

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