Identification of the Knowledge Trajectory of Internet of Vehicles: From the Perspective of Main Path Analysis and Topic Analysis
The Internet of Vehicles (IoV), as the cornerstone of intelligent transportation systems, is gradually attracting attention and accumulated a large amount of literature. Therefore, this article employs citation analysis and topic analysis to analyze the research in the IoV field, revealing the knowledge evolution trajectory and development dynamics. The study selects 10 909 documents from the Web of Science core collection. Through main path analysis, the study identifies the knowledge trajectory of “from Intelligent transportation technology to agent and communication technology to blockchain and security.” In topic analysis, important topics, such as machine learning, autonomous vehicles, simulation, security, and smart cities are identified. Meanwhile, three topic areas machine learning and traffic prediction, simulation and autonomous vehicles, and security and road vehicles are obtained. Our research not only contribute to the advancement of academic research in the IoV field but also provide significant references for the innovation and development of related industries.
Authors
- Zhaoping Yan (ORCID: https://orcid.org/0000-0001-8198-5574)
- Bo Xiang (ORCID: https://orcid.org/0000-0002-9456-7512)
- Dejian Yu (ORCID: https://orcid.org/0000-0003-2796-9148)
- Jin Shi (ORCID: https://orcid.org/0000-0002-1621-6944)
Institutions
- Nanjing Audit University (CN)
- Nanjing University (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1109/jiot.2024.3508740
- Primary Topic
- Medical Research and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00