This study analyzed and synthesized the current state of research on emotion perception within intelligent cockpits, aiming to provide valuable insights for designing, developing, and optimizing emotionally adaptive cockpit interaction systems. Using the Web of Science Core Collection, this study retrieved relevant publications on emotion recognition in intelligent cockpits from 2010 to 2024. Employing bibliometric tools such as CiteSpace and VOSviewer, we conducted a comprehensive review of the field's research landscape, focusing on publication trends, international collaborations, institutional and author contributions, co-citation analysis, and keyword clustering. The findings reveal that the field of emotion recognition in intelligent cockpits has undergone three distinct phases of quantitative growth. China, the United States, and the United Kingdom have established themselves as leaders in this domain. Current research priorities include optimizing multimodal emotion recognition technologies, developing real-time interactive systems, and applying deep learning and machine learning techniques. Future research directions are anticipated to focus on the integration of affective computing with autonomous driving and vehicular networks, the development of personalized emotion regulation strategies, privacy protection in emotion recognition systems, and the convergence of advanced technologies such as artificial intelligence, the Internet of Things, virtual reality, and augmented reality.
Citation: Lichen Sun, Xu Fang, Hongze Yang, Wenbo Zhong, Bo Li. Visualizing thematic evolution in intelligent cockpit emotion perception: A Bibliometric analysis with CiteSpace and VOSviewer[J]. Networks and Heterogeneous Media, 2025, 20(2): 428-459. doi: 10.3934/nhm.2025020
This study analyzed and synthesized the current state of research on emotion perception within intelligent cockpits, aiming to provide valuable insights for designing, developing, and optimizing emotionally adaptive cockpit interaction systems. Using the Web of Science Core Collection, this study retrieved relevant publications on emotion recognition in intelligent cockpits from 2010 to 2024. Employing bibliometric tools such as CiteSpace and VOSviewer, we conducted a comprehensive review of the field's research landscape, focusing on publication trends, international collaborations, institutional and author contributions, co-citation analysis, and keyword clustering. The findings reveal that the field of emotion recognition in intelligent cockpits has undergone three distinct phases of quantitative growth. China, the United States, and the United Kingdom have established themselves as leaders in this domain. Current research priorities include optimizing multimodal emotion recognition technologies, developing real-time interactive systems, and applying deep learning and machine learning techniques. Future research directions are anticipated to focus on the integration of affective computing with autonomous driving and vehicular networks, the development of personalized emotion regulation strategies, privacy protection in emotion recognition systems, and the convergence of advanced technologies such as artificial intelligence, the Internet of Things, virtual reality, and augmented reality.
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Figures(11) / Tables(7)
Lichen Sun, Xu Fang, Hongze Yang, Wenbo Zhong, Bo Li. Visualizing thematic evolution in intelligent cockpit emotion perception: A Bibliometric analysis with CiteSpace and VOSviewer[J]. Networks and Heterogeneous Media, 2025, 20(2): 428-459. doi: 10.3934/nhm.2025020
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