Emerging Trends in Intelligent Vehicles: The IEEE TIV Perspective

被引:7
作者
Zhang, Hui [1 ]
Guo, Junbo [2 ]
Luo, Guiyang [2 ]
Li, Lingxi [3 ]
Na, Xiaoxiang [4 ]
Wang, Xiao [5 ,6 ]
Teng, Siyu [7 ]
Ma, Siji [8 ]
Li, Yidong [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
[2] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
[3] Indiana Univ Purdue Univ Indianapolis, Dept Elect & Comp Engn, Purdue Sch Engn & Technol, Indianapolis, IN 46202 USA
[4] Univ Cambridge, Dept Engn, Cambridge CB2 1PZ, England
[5] Minist Educ, Engn Res Ctr Autonomous Unmanned Syst Technol, Hefei 230601, Anhui, Peoples R China
[6] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
[7] Hong Kong Baptist Univ, Hong Kong 999077, Peoples R China
[8] Macau Univ Sci & Technol, Fac Innovat Engn, Macau 999078, Peoples R China
来源
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES | 2023年 / 8卷 / 08期
关键词
Bibliographic analysis; collaboration pattern; intelligent vehicles (IV); TRANSPORTATION SYSTEMS; TRANSACTIONS; PREDICTION; AVOIDANCE; EVOLUTION; COLLISION;
D O I
10.1109/TIV.2023.3291457
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article is focused on bibliographic analysis and collaboration pattern analysis of the textpapers published in the IEEE Transactions on Intelligent Vehicles (TIV) from January 2019 to January 2023. We have identified the authors, institutions, and countries/regions that are the most productive and have the highest impact. It is found that research on intelligent vehicles is dominated by researchers and institutions from China. Researchers from the US are the second largest contributor to the transaction, whilst those from Germany rank the third. It is also found that, Fei-Yue Wang, Mohan Manubhai Trivedi, and J. Christian Gerdes are the three most productive and influential authors at IEEE TIV, and the Institute of Automation, Chinese Academy of Sciences, National University of Defense Technology, and the University of California, are three most productive and influential institutions. In addition, three networks are generated (i.e., the co-authorship, co-keyword, and author-keyword) to mine collaboration patterns among authors and keywords. Collaboration relationship between researchers and hot research topics are also investigated. Furthermore, an open-source tool is developed to automatically collect metadata, perform bibliographic analysis, and mine collaboration patterns.
引用
收藏
页码:3983 / 3995
页数:13
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