1. 토픽모델링 기반의 국내외 미래 자동차 연구동향 비교 분석: CASE 키워드 중심으로.
- Author
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정호정, 김건욱, 김나경, 장원준, 정원웅, and 박대영
- Subjects
INDUSTRY 4.0 ,INTERNAL combustion engines ,AUTOMOBILE industry ,AUTONOMOUS vehicles ,MOTOR vehicle driving ,CITY traffic - Abstract
After industrialization in the past, the automobile industry has continued to grow centered on internal combustion engines, but is facing a major change with the recent 4th industrial revolution. Most companies are preparing for the transition to electric vehicles and autonomous driving. Therefore, in this study, topic modeling was performed based on LDA algorithm by collecting 4,002 domestic papers and 68,372 overseas papers that contain keywords related to CASE (Connectivity, Autonomous, Sharing, Electrification), which represent future automobile trends. As a result of the analysis, it was found that domestic research mainly focuses on macroscopic aspects such as traffic infrastructure, urban traffic efficiency, and traffic policy. Through this, the government's technical support for MaaS (Mobility-as-a-Service) is required in the domestic shared car sector, and the need for data opening by means of transportation was presented. It is judged that these analysis results can be used as basic data for the future automobile industry. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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