Incorporating Artificial Intelligence Applications in Flexible Pavements: A Comprehensive Overview

With the advancements witnessed in the domains of data science and soft computing, researchers and practitioners have delved into the exploration and application of artificial intelligence to tackle complexities in various fields in the context of built environments and infrastructure. The road construction industry has shown an important effort in the utilization of machine learning as a prevalent and efficient tool to address intricate aspects related to the design, analysis, and optimization of pavement structures. For this, the use of advanced computational techniques in pavement engineering applications has been proved to signify a promising track for addressing challenges and enhancing the efficiency and effectiveness of methodologies within this field. This work presents a comprehensive state-of-the-art review, thoroughly compiling available literature on advancements and developments in the application of Artificial Intelligence (AI) across various phases of flexible pavement works. These phases include structural design, construction, distress detection, and maintenance. Generally, the effectiveness of artificial intelligence has been demonstrated in tasks such as pavement design, cost analysis, defect detection, and maintenance planning. However, it is worth pointing out that significant challenges still persist in various areas such as data collection, parameter optimization, model transferability, and data annotation. It is essential to highlight the need for increased focus on integrating artificial intelligence techniques into pavement engineering.