Artificial Neural Networks for Flexible Pavement

Abstract

Transportation agencies are primarily responsible for building new roads and maintaining current roads. The main focuses of these agencies are to prioritize maintenance and make significant rehabilitation decisions to handle serious problems facing road authorities. Considerable efforts and an abundance of studies have been performed to determine the nature, mechanisms, test methods, and measurement of pavements for preservation and improvements of roadways. The presented study reports a state-of-the-art review on recent advances in the application of artificial intelligence in various steps of flexible pavement, including pavement construction, performance, cost, and maintenance. Herein, the challenges of gathering large amounts of data, parameter optimization, portability, and low-cost data annotating are discussed. According to the findings, it is suggested that greater attention should be paid to integrating multidisciplinary roadway engineering techniques to address existing challenges and opportunities in the future.