Chat2Scenic: Automated Regulatory Test-Scenario Generation for Autonomous Driving via RAGChat2Scenic：基于RAG的自动驾驶测试场景自动生成框架发布
S 1.7T12 sources2 个来源R2-regulatory R8-noise-penalty cross-source×2
Researchers led by Yuan Gao et al. released Chat2Scenic, an iterative RAG-based framework for automatically generating regulation-compliant test scenarios for autonomous driving validation in simulation environments (arXiv 2607.14387, submitted July 2026).
The framework integrates Retrieval-Augmented Generation with a chatbot interface to convert regulatory descriptions into Domain Specific Language (DSL) scenario scripts, addressing the trade-off between compilation success rates and scalability that previous retrieval or retrieval-assemble methods faced.
The authors released an open benchmark comprising 123 scenarios sourced from NHTSA and United Nations Vehicle Regulations, providing the first publicly available dataset for this task and demonstrating significant improvements in automated scenario generation for autonomous driving validation.