Digital Technologies for Road Maintenance Management: A Narrative Review

Effective road maintenance management is vital in the area of transportation safety and mobility as well as infrastructure sustainability. Nonetheless, the traditional methods of road maintenance involve a large degree of manual work and are rather inefficient and costly in nature. Fortunately, recent developments in the realm of digitalization have provided an opportunity to improve road condition evaluation and prediction, maintenance optimization, and other associated operations. In order to provide an overview of digital technologies used in road maintenance management, six different digital tools, namely, Artificial Intelligence, GIS, IoT, Digital Twin, mobile applications, computer vision, and decision support systems, will be discussed. A narrative review method was employed based on the use of the Scopus database. Initially, 413 articles were found; however, applying pre-determined inclusion/exclusion criteria led to narrowing down the list to 35 papers for further discussion. It is evident from the results that digital technologies can help improve the efficiency of the maintenance process via automatic defect detection and identification, monitoring, predictive analytics, maintenance prioritizing, and lifecycle management. Nevertheless, several drawbacks persist, including data issues, implementation expenses, interoperability, integration, and unavailability of standardized frameworks. Moreover, previous studies focus on exploring each technology individually, which emphasizes the necessity of considering several types of technologies together. In this regard, this literature review offers a detailed analysis of the current applications, advantages, challenges, and future areas of research related to intelligent road maintenance management.