ZhengYinan-AIR/Diffusion-Planner

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1043 stars · 174 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official PyTorch implementation of Diffusion Planner, an ICLR 2025 Oral paper using a DiT-based diffusion model for closed-loop autonomous driving motion planning with flexible classifier guidance. It jointly models prediction and planning as future trajectory generation and achieves real-time (~20Hz) inference on nuPlan without rule-based refinement.

Use cases

• closed-loop motion planning for autonomous vehicles
• diffusion-based trajectory generation
• joint prediction and planning of vehicle behavior
• benchmarking learning-based planners on nuPlan
• research on classifier guidance for planning
• real-time driving policy inference

When to choose

• researching diffusion models for autonomous driving planning
• evaluating learning-based planners in closed-loop nuPlan simulation
• exploring joint prediction-planning architectures
• building on published ICLR 2025 planning research

When to avoid

• production autonomous driving systems without safety certification
• projects requiring a permissive license (no license provided)
• non-research users needing turnkey self-driving software
• planning tasks outside vehicle trajectory domains

Facets

library · maturity active

machine-learning deep-learning simulation autonomous-vehicles machine-learning deep-learning python diffusion-models motion-planning imitation-learning nuplan autonomous-driving trajectory-prediction research-code

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