LLM-Based Operating Systems for Automated Vehicles: A New Perspective

Jingwei Ge, Cheng Chang, Jiawei Zhang, Lingxi Li, Xiaoxiang Na, Yilun Lin, Li Li, Fei-Yue Wang

Abstract: The deployment of large language models (LLMs) brings challenges to intelligent systems because its capability of integrating large-scale training data facilitates contextual reasoning. This paper envisions a revolution of the LLM based (Artificial) Intelligent Operating Systems (IOS, or AIOS) to support the core of automated vehicles. We explain the structure of this LLM-OS and discuss the resulting benefits and implementation difficulties.