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AI交通科学家:大模型驱动的自主交通科研

宫晓燕 戴星原 李芮霖 吕宜生

智能科学与技术学报2026,Vol.8Issue(1):33-46,14.
智能科学与技术学报2026,Vol.8Issue(1):33-46,14.DOI:10.11959/j.issn.2096-6652.202605

AI交通科学家:大模型驱动的自主交通科研

AI transportation scientist:LLM-driven autonomous transportation research

宫晓燕 1戴星原 2李芮霖 3吕宜生4

作者信息

  • 1. 中国科学院自动化研究所多模态人工智能系统全国重点实验室,北京 100190
  • 2. 中国科学院自动化研究所多模态人工智能系统全国重点实验室,北京 100190||道路交通安全管控技术国家工程研究中心,北京 100006
  • 3. 山东交通学院,山东 济南 250357
  • 4. 中国科学院自动化研究所多模态人工智能系统全国重点实验室,北京 100190||澳门科技大学创新工程学院,澳门 999078
  • 折叠

摘要

Abstract

Urban transportation systems are rapidly evolving into CPSS(cyber-physical-social system),driven by the con-tinuous integration of autonomous vehicles,unmanned aerial vehicles,and diverse intelligent agents.This evolution has dramatically increased system complexity,dynamics,and coupling,rendering traditional human-centric research para-digms insufficient for timely understanding and response to fast-evolving system behaviors.To address these challenges,an autonomous framework called"AI Transportation Scientist"was proposed to revolutionize transportation research through parallel intelligence.The architecture leveraged a synergy between large language model and multi-agent system across four functional layers(interaction,cognitive,experimental,and support).At its core,a dynamic routing engine adaptively scheduled intelligent agents to tackle mechanism discovery,strategy validation,and system optimization.By implementing a full-chain collaborative closed loop—encompassing problem identification,simulation,and feedback opti-mization—the framework enabled the autonomous discovery of transportation laws and the continuous evolution of con-trol strategies.This research establishes a scalable technical paradigm for advancing transportation science within CPSS environments,ensuring both efficient problem-solving and innovative strategy iteration.

关键词

社会物理信息系统/平行智能/自主交通科研/交通科学家/自驱实验室

Key words

CPSS/parallel intelligence/autonomous transportation research/transportation scientist/self-driving laboratory

分类

信息技术与安全科学

引用本文复制引用

宫晓燕,戴星原,李芮霖,吕宜生..AI交通科学家:大模型驱动的自主交通科研[J].智能科学与技术学报,2026,8(1):33-46,14.

基金项目

国家自然科学基金项目(No.62271485,No.62303462) (No.62271485,No.62303462)

道路交通安全管控技术国家工程研究中心开放课题(No.2024GCZXKFKT11A) (No.2024GCZXKFKT11A)

山东省交通运输厅科技计划项目(No.2024B70) (No.2024B70)

山东高速集团有限公司科技计划项目(No.HS2023B044)The National Natural Science Foundation of China(No.62271485,No.62303462),Open Project of the National Engineering Research Center for Road Traffic Safety Management Technology(No.2024GCZXKFKT11A),The Science and Technology Project of Shandong Provincial Department of Transportation(No.2024B70),SDHS Science and Technology Project(No.HS2023B044) (No.HS2023B044)

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