首页|Parallel Driving with Big Models and Foundation Intelligence in Cyber-Physical-Social Spaces

Parallel Driving with Big Models and Foundation Intelligence in Cyber-Physical-Social Spaces

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Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles(CAVs).On the one hand,these breakthroughs have significantly advanced the development of intelligent transportation systems(ITSs);on the other hand,these new traffic participants introduce more complex and uncertain elements to ITSs from the social space.Digital twins(DTs)provide real-time,data-driven,precise modeling for constructing the digital mapping of physical-world ITSs.Meanwhile,the metaverse integrates emerging technologies such as virtual reality/mixed reality,artificial intelligence,and DTs to model and explore how to realize improved sustainability,increased efficiency,and enhanced safety.More recently,as a leading effort toward general artificial intelligence,the concept of foundation model was proposed and has achieved significant success,showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains.In this article,we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces,which integrate metaverse and DTs to construct a parallel training space for CAVs,and present a comprehensive elucidation of the crucial characteristics and operational mechanisms.Beyond providing the infrastructure and foundation intelligence of big models for parallel driving,this article also discusses future trends and potential research directions,and the"6S"goals of parallel driving.

Xiao Wang、Jun Huang、Yonglin Tian、Chen Sun、Lie Yang、Shanhe Lou、Chen Lv、Changyin Sun、Fei-Yue Wang

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School of Artificial Intelligence,Anhui University,Hefei,China

Macau University of Science and Technology,Macao,China

State Key Laboratory for Management and Control of Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing,China

MVSLab,Department of Mechanical and Mechatronics Engineering,University of Waterloo,200 University Ave West,Waterloo,ON N2L3G1,Canada

School of Mechanical and Aerospace Engineering,Nanyang Technological University,Singapore,Singapore

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National Natural Science Foundation of ChinaUniversity Scientifc Research Program of Anhui ProvinceIntel Collaborative Research Institute for Intelligent and Automated Connected Vehicles(A Unified Approach for Transport AutomatNational Natural Science Foundation of ChinaGuangdong Key Area R&D PlanGuangdong Key Area R&D Plan

621733292023AH020005621733292020B09090500032020

2024

10.34133/research.0349

研究(英文)

研究(英文)

CSTPCD
ISSN：
年,卷(期)：2024.2024(2)
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