Comprehensive Pavement Deterioration Assessment Using Fuzzy Analytical Hierarchy Process

Abstract Pavement evaluation represents the critical foundation of effective pavement management systems. Developing a sophisticated deterioration index is crucial for authorities to strategically allocate maintenance and rehabilitation budgets. Advanced countries have implemented various single and combined condition indices based on extensive pavement databases. Unfortunately, developing nations often lack comprehensive condition data, resulting in underdeveloped evaluation metrics and consequently, suboptimal budget allocation for preservation activities. This study develops an integrated overall deterioration index (ODI) of pavement using weighted combinations of four key assessment categories. The first category examines pavement condition index (PCI), including various cracking patterns, deformations, surface defects, patching/potholes, and edge deterioration, surface texture, load bearing capacity, layer thickness, material properties, drainage conditions, climate change, pavement age, and traffic loading. The second focuses on international roughness index (IRI) metrics such as roughness, and comfort levels. The third addresses falling weight deflectometer (FWD) including deflection measurements. The fourth examines friction number (FN) like skid resistance. The weighting methodology employs fuzzy analytical hierarchy process through expert panel evaluations. Analysis reveals PCI as the predominant factor (weight: 0.439), with IRI and FWD ranking second and third (weights: 0.15 and 0.318 respectively). These weightings demonstrate engineering validity across the case study. The resulting composite index offers a holistic assessment of pavement deterioration applicable to maintenance planning frameworks. A model performance was made using the long-term pavement performance (LTPP) and it proved the validity of the model.