1Master’s Student, Dept. of Industrial Engineering, Yonsei University, Seoul, Republic of Korea
2Postdoctoral Researcher, Dept. of Industrial Engineering, Yonsei University, Seoul, Republic of Korea
3PhD Candidate, Dept. of Industrial Engineering, Yonsei University, Seoul, Republic of Korea
4Integrated Master’s and Ph.D. Student, Dept. of Industrial Engineering, Yonsei University, Republic of Korea
5Professor, Dept. of Industrial Engineering, Yonsei University, Seoul, Republic of Korea
Correspondence to Hee Jun Park, E-mail: h.park@yonsei.ac.kr
Volume 19, Number 4, Pages 183-208, December 2024.
The Journal of Intellectual Property 2024;19(4):183-208. https://doi.org/10.34122/jip.2024.19.4.8
Received on October 15, 2024, Revised on November 21, 2024, Accepted on December 05, 2024, Published on December 30, 2024.
Copyright © 2024 Korea Institute of Intellectual Property.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
This study investigates trends in autonomous vehicle technology by employing hierarchical clustering based on BERTopic. The study analyzes a total of 9,164 patents registered and expired between 1990 and 2024. The analysis identifies key topics and technological components, including sub-technologies that pose challenges for classification within existing patent frameworks. Notably, the study finds a rapid increase in the use of thermal management and cooling system management technology, which is essential for high-performance vehicle design.
The findings indicate that the BERTopic approach is an effective methodology for patent classification, facilitating time and cost savings through automated text analysis. The study also offers insights into the detailed technologies relevant to the evolving patent classification system of the 4th Industrial Revolution. These insights offer valuable guidance for R&D strategy development, patent portfolio management, and strategic decision-making in the autonomous vehicle sector.
Patent analysis, Autonomous vehicles, Topic modeling, Hierarchical clustering, Technology trend analysis
The authors declared no conflicts of interest.
The author received manuscript fees for this article from Korea Institute of Intellectual Property.