Recent advancements on artificial intelligence in revolutionizing transportation geotechnics: Integration and innovations (2013–2025)

Transportation geotechnics deals with geotechnical challenges faced in construction and maintenance of transportation infrastructure such as roads, highways, railways, underground transit systems, tunnels, airfields, and waterways. The inherent complexity of soil and rock behavior introduces significant uncertainties in material modeling, and during the past few decades researchers have increasingly turned to use of artificial intelligence (AI) methods to address these challenges in transportation geotechnics, effectively predicting complex and nonlinear relationships, conducting data analysis and interpretation, assessing and predicting risks, and implementing smart construction and monitoring techniques. This paper provides a comprehensive overview of recent advancements in effective AI methods used in transportation geotechnics from 2013 to 2025. It builds upon the review paper published by one of the authors at the University of Minho in 2013. The paper highlights key areas in which AI methods have been extensively applied and explores case studies and success stories, demonstrating the application of AI in this field. It also emphasizes the proficiency of these methods in addressing complex challenges, especially in dealing with highly nonlinear relationships, conducting data analysis and interpretation, assessing risks, and meeting demanding optimization requirements.