Comprehensive review and future perspectives on prediction and mitigation of tunnel-induced ground settlement: A bibliometric analysis and methodological overview (2002–2022)

• A comprehensive review of 1209 research papers on tunnel-induced ground settlement (2002–2022). • Applied CiteSpace and VOSviewer to map collaborative networks in a novel way. • Explored empirical, analytical, numerical, and intelligent methods for ground settlement prediction. • Revealed the dominance of the shield method and discussed measures for controlling ground settlement. • Pointed to the future by emphasizing the integration of AI, big data, and sensor technology in ground settlement research. Predicting and controlling tunnel-induced ground settlement is crucial for ensuring safety and minimizing environmental impact. However, current research methods are varied, each with specific conditions and limitations, making a comprehensive review necessary. In this paper, 1209 research papers on tunnel-induced ground settlement (2002–2022) collected from the Web of Science Core Collection (WoSCC) were analyzed using CiteSpace and VOSviewer bibliometric analysis techniques. The analysis findings reveal three developmental stages in tunnel-induced ground settlement research. Additionally, knowledge maps are generated, including collaborative network maps depicting countries, institutions, and authors, keyword co-occurrence maps, and time trend maps. In order to comprehensively summarize the research progress in the field, the four prediction methods: empirical, analytical, numerical, and intelligent methods, are discussed in depth. Subsequently, the common methods of tunnel construction are introduced, and the measures to control ground settlement during shield construction are discussed. Finally, the paper presents the main future research directions in the field of ground settlement. Different technological advancements, with a particular emphasis on subsidence monitoring, highlight the significance of integrating multiple technologies. The application of multi-technology integration, including artificial intelligence, big data analysis, and sensor technology, is identified as a crucial direction for future development.