Development of an automated pavement condition assessment tool based on Ge-Road mobile monitoring data and the ASTM D6433 methodology

Abstract

This article investigates the possibilities of processing pavement distress data collected through the Ge-Road mobile application and automatically calculating the Pavement Condition Index (PCI) in accordance with the ASTM D6433 international standard. The study focuses on the digitalization of pavement distress assessment procedures, the reduction of human-related calculation errors, and the development of an Excel-based automated evaluation tool that is practical and accessible for road maintenance organizations. The proposed approach enables rapid assessment of pavement conditions, accurate identification of maintenance needs, and improved efficiency in operational decision-making processes. The results demonstrate the potential of integrating mobile data collection and automated analysis tools to enhance pavement management practices and support more effective maintenance planning.