Integration of GIS and GPS as a decision support tool in a GAMS-based network-level pavement maintenance optimisation system

The transportation system is crucial for a country's growth, with road transport connecting villages and cities, especially in developing countries like India. Neglecting road maintenance leads to severe pavement impairment and reconstruction expenses, affecting the economy. Government challenges include deteriorating urban roads and inadequate funding, resulting in subjective, ad hoc maintenance decisions. An effective pavement management system is essential for optimal maintenance and rehabilitation. This study assesses urban road sections, clusters them, develops performance prediction models, and identifies maintenance treatments to create a decision support tool. Distresses data collected over 6 years, pre and post-monsoon, were used to calculate pavement condition indices. Sections were grouped using the K-means algorithm for better modeling, and a deterministic deterioration model estimated pavement conditions over time. Optimized maintenance treatments for 5 years were determined using Generic Algebraic Modeling System software. A user-friendly geographic information system interface graphically represents the road network, incorporating collected data and optimized treatments.