Poutine: Vision-Language-Trajectory Pre-Training and Reinforcement Learning Post-Training Enable Robust End-to-End Autonomous Driving

A new method called Poutine is making waves in the field of autonomous driving by addressing the challenges of maintaining good driving behavior in unusual scenarios. By utilizing a powerful vision-language model, Poutine treats these out-of-distribution situations as logical reasoning tasks, showcasing the potential of large-language models in enhancing the safety and reliability of self-driving cars. This advancement is significant as it could lead to more robust autonomous systems that can better navigate unpredictable environments.