Advanced computer technologies such as big data, Artificial Intelligence (AI), cloud computing, digital twins, and edge computing have been applied in various fields as digitalization has progressed. To study the status of the application of digital twins in the combination with AI, this paper classifies the applications and prospects of AI in digital twins by studying the research results of the current published literature. We discuss the application status of digital twins in the four areas of aerospace, intelligent manufacturing in production workshops, unmanned vehicles, and smart city transportation, and we review the current challenges and  topics that need to be looked forward to in the future. It was found that the integration of digital twins and AI has significant effects in aerospace flight detection simulation, failure warning, aircraft assembly, and even unmanned flight. In the virtual simulation test of automobile autonomous driving, it can save 80% of the time and cost, and the same road conditions reduce the parameter scale of the actual vehicle dynamics model and greatly improve the test accuracy. In the intelligent manufacturing of production workshops, the establishment of a virtual workplace environment can provide timely fault warning, extend the service life of the equipment, and ensure the overall workshop operational safety. In smart city traffic, the real road environment is simulated, and traffic accidents are restored, so that the traffic situation is clear and efficient, and urban traffic management can be carried out quickly and accurately. Finally, we looked forward to the future of digital twins and AI, hoping to provide a reference for future research in related fields.

Applications of Artificial Intelligence in Transport:

An Overview

Rusul Abduljabbar *, Hussein Dia *, Sohani Liyanage and Saeed Asadi Bagloee

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Department of Civil and Construction Engineering; Swinburne University of Technology,

Hawthorn, VIC 3122, Australia; sliyanage@swin.edu.au (S.L.); sasadibagloee@swin.edu.au (S.A.B.)

* Correspondence: rabduljabbar@swin.edu.au (R.A.); hdia@swin.edu.au (H.D.);

Tel.: +61-432-299-979 (R.A.); +61-392-145-280 (H.D.)

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数字孪生五维模型及十大领域应用

陶 飞 刘蔚然 张 萌 胡天亮 戚庆林 张 贺 隋芳媛 王 田 徐 慧 黄祖广 马 昕 张连超 程江峰 姚念奎 易旺民 朱恺真/ 张新生/ 孟凡军* 金小辉

刘中兵 何立荣 程 辉 周二专 李 洋 吕 倩 罗椅民

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北京航空航天大学 自动化科学与电气工程学院 北京

山东大学 机械工程学院 山东 济南 北自所 北京 科技发展有限公司 北京 国家机床质量监督检验中心 北京 沈阳飞机设计研究所 辽宁 沈阳 ( 中国空间技术研究院 北京卫星环境工程研究所 北京 / 机械工业第六设计研究院有限公司 河南 郑州 / * 中国兵器工业集团第五五研究所 吉林 长春 北京航天拓扑高科技有限公司 北京 /( 北京航天万源科技有限公司 北京 /( 北京必可测科技股份有限公司 北京 * 上海航天设备制造总厂 上海 国网电力科学研究院 北京 国网电子商务有限公司 光伏云事业部 北京 中国电子科技集团第十研究所 四川 成都 ( ( ( 国家康复辅具研究中心 发展战略研究所 北京 /(

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OPEN CARS

Lothar Determann† & Bruce Perens††

Open Source Software and the “Private-Collective” Innovation Model: Issues for Organization Science

Eric von Hippel •Geor g von Krogh

Sloan School of Management, Massachusetts Institute of Technology, 50 Memorial Drive,

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Cambridge, Massachusetts 02141

Institute of Management, University of St. Gallen, Dufourstrasse 48, CH-9010 St. Gallen, Switzerland

evhippel@mit.edu • georg.vonkrogh@unisg.ch

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Research Article

Reengineering Aircraft Structural Life Prediction Using a Digital Twin

Eric J. Tuegel,1 Anthony R. Ingraffea,2 Thomas G. Eason,1 and S.Michael Spottswood1

Toward a Digital Twin for real-time geometry assurance in individualized production

Rikard So¨derberg (2)a,*, Kristina Wa¨rmefjord a, Johan S. Carlson b, Lars Lindkvist a

a Chalmers University of Technology, Department of Product and Production Development, SE 412-96 Gothenburg, Sweden

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b Fraunhofer-Chalmers Centre for Industrial Mathematics, SE-412 88 Gothenburg, Sweden

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The Digital Twin: Realizing the Cyber-Physical Production System for Industry 4.0

Thomas H.-J. Uhlemanna*, Christian Lehmanna, Rolf Steinhilpera

aFraunhofer Project Group Process Innovation at the Chair of Manufacturing and Remanufacturing Technology, Bayreuth University, 95447 Germany

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* Corresponding author. Tel.: +49-921-785-16323; fax:+49-921-785-16105. E-mail address: thomas.uhlemann@uni-bayreuth.de

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