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  • 标题:A Study of Bibliometric Trends in Automotive Human-Machine Interfaces
  • 本地全文:下载
  • 作者:Zhang, Xu ; Liao, Xi-Peng ; Tu, Jui-Che
  • 期刊名称:Sustainability
  • 印刷版ISSN:2071-1050
  • 出版年度:2022
  • 卷号:14
  • 期号:15
  • 页码:1-27
  • DOI:10.3390/su14159262
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:With the development of autonomous driving technology and the internet, automotive human–machine interface (HMI) technology has become an important part of contemporary automotive design. Currently, global automakers are designing a variety of innovative in-car HMIs that illustrate the direction of automotive design in the new era from the perspective of technological aesthetics and experience design. However, sleek designs and innovative experience methods must be built on the basis of safety. Therefore, it is necessary to summarize existing research in the field of automotive HMI and construct a literature review of automotive design research. In this paper, literature on automotive HMI from the Scopus database was analyzed using bibliometric methods such as descriptive analysis, keyword co-occurrence, and literature co-citation network analysis. The final mapping analysis revealed that the current automotive HMI research literature primarily focuses on user research, interface research, external environment research, and technology implementation research related to automotive HMI. The three main stages of automotive HMI research include conceptual construction, system and technology refinement, and user perception research from the perspective of driver assistance and information recognition. Additionally, burst detection suggests that future research should focus on driver assistance, trust levels, and e-HMI information communication.
  • 关键词:human–computer interface; automotive; driver assistance; information recognition; bibliometrics; collaborative networks; topic evolution
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