Bibliometric Analysis and Visualization of Research in Driver Fatigue Detection

Given that driver fatigue plays a major role in causing traffic accidents, conducting research on fatigue detection holds substantial practical significance with the goal of increasing road safety while decreasing accident rates. To identify research hotspots and anticipate future trends in this field, this study conducted a bibliometric analysis to examine the evolution of fatigue driving detection research. On July 1, 2025, a total of 477 relevant articles were collected and screened from the Web of Science Core Collection database. Utilizing online bibliometric analysis platforms, VOSviewer 1.6.20, Citespace 6.3.1, and R-based bibliometrix, information on publications, countries, institutions, journals, and keywords related to this field was evaluated and visualized. This approach revealed the current state of applications in fatigue driving detection and provided a detailed analysis of the latest research hotspots and trends. The findings offer systematic data to support subsequent research in the field of fatigue driving, filling gaps at both national and international levels, and provide valuable references for the development of fatigue detection technologies and driver assistance systems.

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Publication Details

Journal
International Journal of Pattern Recognition and Artificial Intelligence
Published
2025-09-27
DOI
https://doi.org/10.1142/s021800142557023x
Primary Topic
Fuzzy Logic and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Bibliometric Analysis and Visualization of Research in Driver Fatigue Detection

Shuxi Chen, Qiu Jianlin, Min Bingyuan, Sun Yiyang
International Journal of Pattern Recognition and Artificial Intelligence
Fuzzy Logic and Control Systems
article

Bibliometric Analysis and Visualization of Research in Driver Fatigue Detection

Shuxi Chen, Qiu Jianlin, Min Bingyuan, Sun Yiyang
article en

Abstract

Given that driver fatigue plays a major role in causing traffic accidents, conducting research on fatigue detection holds substantial practical significance with the goal of increasing road safety while decreasing accident rates. To identify research hotspots and anticipate future trends in this field, this study conducted a bibliometric analysis to examine the evolution of fatigue driving detection research. On July 1, 2025, a total of 477 relevant articles were collected and screened from the Web of Science Core Collection database. Utilizing online bibliometric analysis platforms, VOSviewer 1.6.20, Citespace 6.3.1, and R-based bibliometrix, information on publications, countries, institutions, journals, and keywords related to this field was evaluated and visualized. This approach revealed the current state of applications in fatigue driving detection and provided a detailed analysis of the latest research hotspots and trends. The findings offer systematic data to support subsequent research in the field of fatigue driving, filling gaps at both national and international levels, and provide valuable references for the development of fatigue detection technologies and driver assistance systems.

International Journal of Pattern Recognition and Artificial IntelligenceVol. 39(16)
Nantong University (CN), Mokwon University (KR), Nantong Science and Technology Bureau (CN)
Openalex Percentile: Top 86%
Fuzzy Logic and Control Systems
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Bibliometric Analysis and Visualization of Research in Driver Fatigue Detection — Shuxi Chen, Qiu Jianlin, et al. · International Journal of Pattern Recognition and Artificial Intelligence (2025) | TGRS Research Map | TGRS