A bibliometric review of research on driver fatigue under conditional automated driving

In order to comprehend the research hotspots and development trends in the field of driver fatigue on conditional automated driving, from the perspective of driver fatigue state and automated driving function, multiple topic words were combined to retrieve relevant articles from the core collection database of Web of Science. A total of 231 articles were retrieved after the data screening from 2010 to 2023, and the literature analysis was conducted from the perspective of annual distribution, countries and institutions distribution, source publications distribution. Then, the VOSviewer and CiteSpace software were used to analyze the research topic and frontiers of literatures considering literature co-citation, keyword co-occurrence, and keyword burst. The results indicated that the USA, China, and Germany are the top three countries involved in driver fatigue research under conditional automated driving. Technical University of Munich is the institution that published the largest number of articles in this field. Accident Analysis & Prevention, IEEE Transactions on Intelligent Transportation Systems, and Transportation Research Part F: Traffic Psychology and Behaviour are the top three journals that scholars selected to submit articles. The relevant research topics in the field of driver fatigue under conditional automated driving mainly including (a) fatigue detection method, and the effect of automated duration on driver state, (b) the effect of non-driving related tasks (NDRT) on driver behavior and fatigue state, (c) the influential indicators for fatigue from manual driving to conditional automated driving, and (d) the difference of driving behavior and fatigue state between manual driving and conditional automated driving. With the phenomenon of keywords burst, professional drivers, takeover performance, monitoring tasks, and deep learning have become the research frontiers and hotspots. In summary, this study revealed the research topic, frontiers and development trend in the field of driver fatigue under conditional automated driving through bibliometric and structured network analysis. This study hopes to offer valuable insights for future research directions, highlighting the importance of fatigue detection methods, the impact of automated driving duration, the role of non-driving related tasks, and the transition from manual to conditional automated driving condition.