Foundation Models for Transportation Intelligence: ITS Convergence in TransVerse
文献类型：期刊论文
| 作者 | Zhao, Chen2 ; Dai, Xingyuan3; Yisheng Lv3; Tian, Yonglin1; Ren, Yuhai4; Wang, Fei-Yue5
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| 刊名 | IEEE Intelligent Systems
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| 出版日期 | 2022-11 |
| 卷号 | 37期号:6页码:77-82 |
| 英文摘要 | 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. |
| 源URL | [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.Waytous Incorporation, Beijing, 100083, China 2.University of Chinese Academy of Sciences, Beijing, 100049, China 3.CASIA, Beijing, 100190, China 4.North Automatic Control Technology Institute, Taiyuan, 030006, China 5.Macau University of Science and Technology, Macao, 999078, China |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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