Technological advances in flexible pavement assessment methods: a literature review

Abstract

This research analyses the technological advances in flexible pavement assessment methods, focusing especially on three key indicators: the Pavement Condition Index (PCI), the International Roughness Index (IRI) and the Pavement Serviceability Index (PSI). The main objective of this research was to examine how new technologies transform road infrastructure management and improve the accuracy and efficiency in the assessment of pavement condition. The research is bibliographical and documentary with a deductive method, qualitative approach and applied orientation. It is descriptive and explanatory, with a non-experimental, transversal and retrospective design. For data collection, the documentary review technique was used and the instrument was retrospective based on a review of scientific articles published in the Scopus database between 2019 and 2025. The results obtained show that the incorporation of techniques such as machine learning, neural networks and specialized algorithms allow for a significant improvement in the accuracy of the prediction of these indices, surpassing traditional methodologies. In addition, the use of technologies such as computer vision and drones transform pavement inspection and allow for faster, more precise and automated analysis. The use of smart sensors and Internet of Things (IoT) technologies facilitate continuous and real-time monitoring of road infrastructure, optimizing resources for its maintenance and contributing to extending the useful life of pavements.