Emerging Trends in Intelligent Vehicles: The IEEE TIV Perspective
Hui Zhang, Junbo Guo, Guiyang Luo, Lingxi Li, Xiaoxiang Na, Xiao Wang, Siyu Teng, Siji Ma, Yidong Li
Abstract
This article is focused on bibliographic analysis and collaboration pattern analysis of the <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">text</uri> papers 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.