Lifecycle and Risk-Based Optimisation Framework for Condition-Triggered Maintenance of Flexible Pavement Networks Under Indian Traffic and Climatic Conditions

Abstract

Traditional highway maintenance in India relies on fixed periodic resurfacing cycles, leading to resource inefficiencies and delayed repairs. This paper presents a framework for maximizing flexible pavement network life cycles through condition-triggered and risk-weighted optimization. The methodology integrates Indian Roads Congress (IRC) assessment techniques, specifically IRC:115 for structural evaluation and IRC:37 for design, with lifecycle economics and probabilistic risk modelling. Deterioration models were calibrated to account for tropical monsoon climates and Indian traffic heterogeneity.
The framework was validated through a 20-year case study of a 48-kilometer State Highway near Chennai, Tamil Nadu. Statistical validation via Monte Carlo simulation showed the optimized solution led to an 18% reduction in discounted life-cycle costs compared to traditional periodic resurfacing. Key improvements included a 26% increase in serviceable network duration and a 45% decrease in major structural strengthening interventions.
By shifting from age-based cycles to state-dependent optimization, this framework provides a robust and feasible pathway for Indian highway agencies to implement performance-based asset management. The results confirm that considering functional indices and structural assessments ensures fiscal resilience under budget constraints.