基于 LLM 的自动驾驶汽车操作系统：新视角

IF 14 1区工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IEEE Transactions on Intelligent Vehicles Pub Date : 2024-04-01 DOI:10.1109/TIV.2024.3399813

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

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引用次数: 0

摘要

大型语言模型（LLMs）的部署给智能系统带来了挑战，因为其整合大规模训练数据的能力有助于上下文推理。本文设想了一场基于 LLM 的（人工）智能操作系统（IOS，或 AIOS）革命，以支持自动驾驶汽车的核心。我们解释了这种 LLM-OS 的结构，并讨论了由此带来的好处和实施上的困难。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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来源期刊

IEEE Transactions on Intelligent Vehicles Mathematics-Control and Optimization

CiteScore

12.10

自引率

13.40%

发文量

177

期刊介绍： The IEEE Transactions on Intelligent Vehicles (T-IV) is a premier platform for publishing peer-reviewed articles that present innovative research concepts, application results, significant theoretical findings, and application case studies in the field of intelligent vehicles. With a particular emphasis on automated vehicles within roadway environments, T-IV aims to raise awareness of pressing research and application challenges. Our focus is on providing critical information to the intelligent vehicle community, serving as a dissemination vehicle for IEEE ITS Society members and others interested in learning about the state-of-the-art developments and progress in research and applications related to intelligent vehicles. Join us in advancing knowledge and innovation in this dynamic field.