Recent advancements in autonomous vehicles (AVs) leverage Large Language Models (LLMs) to perform well in normal driving scenarios. However, ensuring safety in dynamic, high-risk environments and managing safety-critical long-tail events remains a significant challenge. To address these issues, we propose SafeDrive, a knowledge- and data-driven risk-sensitive decision-making framework, to enhance AV safety and adaptability. The proposed framework introduces a modular system comprising: (1) a Risk Module for compre…