The 1st Workshop on Distillation of Foundation Models for Autonomous Driving (WDFM-AD) aims to advance the deployment of large foundation models—such as vision-language models (VLMs) and generative AI (GenAI) models—within autonomous driving systems through efficient distillation techniques. Building on the momentum of prior workshops focused on large language and vision models for autonomous driving, WDFM-AD provides a dedicated platform for researchers and industry practitioners to explore methods that bridge cutting-edge foundation model research with real-world deployment, particularly under the stringent latency and resource constraints of autonomous vehicles. By addressing the challenges of compressing, aligning, and deploying foundation models for self-driving, WDFM-AD seeks to accelerate their safe, efficient, and scalable integration into next-generation autonomous driving systems.