OmniDrive-R1: Advancing Autonomous Driving with Trustworthy AI

This research explores the application of reinforcement learning and multi-modal chain-of-thought in autonomous driving, aiming to enhance trustworthiness. The paper's contribution lies in its novel approach to integrating vision and language for more reliable decision-making in self-driving systems.

• •Focuses on improving the trustworthiness of vision-language models for autonomous driving.
• •Utilizes reinforcement learning and chain-of-thought reasoning.
• •Proposes an interleaved multi-modal approach for enhanced decision making.