Knowledge Commons of Institute of Automation,CAS
Foundation Models for Transportation Intelligence: ITS Convergence in TransVerse | |
Zhao, Chen1![]() ![]() ![]() ![]() ![]() | |
发表期刊 | IEEE Intelligent Systems
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2022-11 | |
卷号 | 37期号:6页码:77-82 |
摘要 | Smart cities are our aspiration for a better life where transportation intelligence is indispensable. Recent technological advances in intelligent transportation systems have opened up new possibilities for smart mobility in smart cities. Here we present TengYun, a transportation foundation model designed and developed with parallel learning and federated intelligence for our transportation metaverse called TransVerse. TengYun enables decentralized/distributed autonomous organizations with decentralized/ distributed operations, as well as various federated technologies, from federated security, federated control, federated management, federated services, to federated ecology for transportation intelligence in smart cities. An example for a federation of transportation transformers is discussed for illustrating the operating procedure of TengYun. |
收录类别 | SCI |
七大方向——子方向分类 | 平行管理与控制 |
国重实验室规划方向分类 | 多智能体决策 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/56520 |
专题 | 多模态人工智能系统全国重点实验室 |
通讯作者 | Dai, Xingyuan |
作者单位 | 1.University of Chinese Academy of Sciences, Beijing, 100049, China 2.CASIA, Beijing, 100190, China 3.Waytous Incorporation, Beijing, 100083, China 4.North Automatic Control Technology Institute, Taiyuan, 030006, China 5.Macau University of Science and Technology, Macao, 999078, China |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zhao, Chen,Dai, Xingyuan,Yisheng Lv,et al. Foundation Models for Transportation Intelligence: ITS Convergence in TransVerse[J]. IEEE Intelligent Systems,2022,37(6):77-82. |
APA | Zhao, Chen,Dai, Xingyuan,Yisheng Lv,Tian, Yonglin,Ren, Yuhai,&Wang, Fei-Yue.(2022).Foundation Models for Transportation Intelligence: ITS Convergence in TransVerse.IEEE Intelligent Systems,37(6),77-82. |
MLA | Zhao, Chen,et al."Foundation Models for Transportation Intelligence: ITS Convergence in TransVerse".IEEE Intelligent Systems 37.6(2022):77-82. |
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