Emerging Trends in Intelligent Vehicles: The IEEE TIV Perspective

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. The authors 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.

• Record URL:
  http://dx.doi.org/10.1109/TIV.2023.3291457
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23798858
• Supplemental Notes:
  • Copyright © 2023, IEEE.
• Authors:
  • Zhang, Hui
  • Guo, Junbo
  • Luo, Guiyang
  • Li, Lingxi
  • Na, Xiaoxiang
  • Wang, Xiao
  • Teng, Siyu
  • Ma, Siji
  • Li, Yidong
• Publication Date: 2023-8

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: pp 3983-3995
• Serial:
  • IEEE Transactions on Intelligent Vehicles
  • Volume: 8
  • Issue Number: 8
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 2379-8858
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274857

Subject/Index Terms

• TRT Terms: Cooperation; Intelligent transportation systems; Intelligent vehicles; Market research; Metadata; Traffic safety
• Subject Areas: Highways; Research; Vehicles and Equipment;

Filing Info

• Accession Number: 01900719
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 28 2023 10:37AM