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 (LLM) 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.
Topics & Concepts
Software deploymentComputer sciencePerspective (graphical)Core (optical fiber)Systems engineeringArtificial intelligenceSoftware engineeringEngineeringTelecommunicationsSoftware System Performance and ReliabilitySoftware Testing and Debugging TechniquesAutonomous Vehicle Technology and Safety