Pavement Condition Assessment Using Fuzzy Analytic Hierarchy Process

This study develops a fuzzy mathematical analysis called the Fuzzy Analytic Hierarchy Process (FAHP) for Pavement Condition Assessment (PCA) and prioritization by considering the functional and structural evaluation of pavement as well as traffic volume. The Pavement Condition Index (PCI), characteristic deflection, International Roughness Index (IRI), and Commercial Vehicles Per Day (CVPD) are identified as four performance indicators for PCA. Software for executing FAHP is developed using Python, providing performance indicator values as inputs, and the deliverable is the Fuzzy Pavement Priority Index (FPPI). The selected stretches of National Highway (NH) 66, State Highway (SH) 75, SH 61, and SH 51, in the Thrissur district of Kerala, India is prioritized from the Maintenance and Rehabilitation (M & R) aspect based on FPPI values from the software. FAHP, being a combination of the Analytic Hierarchy Process (AHP) and fuzzy logic, measures the degree of consistency in the judgments provided by a decision-maker and captures the subjectivity inherent in human judgment. The results demonstrate that the collected data serves as a good estimator to prioritize the stretches for M & R purposes. The proposed method, being a more scientific approach, serves as a base model for PCA and the developed software delivers FPPI values suitable for performing the differential ranking of stretches.