International Research Progress on Highway Tunnel Traffic Safety Based on Bibliometric Analysis

In order to systematically analyze and comprehensively summarize the current state of research and development trends of highway tunnel traffic safety, relevant English languageliterature published between 2000 and 2022 in this field is retrieved from the Web of Science Core Collection database. Using VOSviewer software, the literature is visually presented and analyzed to create a knowledge map of major research themes and hotspots in highway tunnel traffic safety. The research status, challenges, and development trends in this field are summarized. The results indicate that the annual publication volume of research literature on traffic safety in highway tunnels shows an overall upward trend. In terms of contributions, China leads among countries, Tongji University among institutions, and "Tunnelling and Underground Space Technology" among journals. Current research hotspots in highway tunnel traffic safety focus on topics such as the analysis ofaccident characteristics in highway tunnels, driving environment and driving performance in highway tunnels, highway tunnel lighting and its impact on driving safety, and traffic facilities in highway tunnels and their relving in highway tunnels, levation to driving safety. However, there are limitations in the evaluation methods and technical standards for highway tunnel traffic safety. The consideration of factors in the evaluation system is one-sided and inconsistent, the accuracy and validity of data sources and mathematical models still need to be improved, and the application effects of intelligent transportation technologies on highway tunnel traffic safety need further investigation. Future research in this field should prioritize the development of methods and evaluation models to enhance the driving environment in highway tunnels, considering different levels of demand. It should also focus on macro-level situation analysis and micro-level individual analysis of driving in highway tunnels, leveraging multi-source, heterogeneous, and big data. Additionally, research should study driving risk perception models and control strategies for highway tunnels, utilizing machine learning and intelligent connected vehicle technologies.