Chat2Scenic: Iterative RAG Framework for Autonomous Driving Scenario Generation

Jul 17, 2026

Chat2Scenic introduces an iterative retrieval-augmented generation (RAG) framework that generates executable scenario scripts for autonomous driving testing directly from regulatory descriptions. The system achieves a 76.42% compilation success rate and 58.17% framework accuracy, substantially outperforming previous methods. The authors also provide an open benchmark and have released their code as open source.

Why it matters: This work advances the automation of regulation-compliant scenario generation, addressing a key challenge in validating autonomous driving systems.

Full story at: arXiv AI/ML ↗