Development of Statistical Model For Predicting Flexible Pavement Deterioration Due To Traffic Loading

Abstract

Flexible pavements are critical transportation components but are highly susceptible to deterioration caused by traffic loading, pavement conditions, and environmental factors. This study develops a predictive model to estimate pothole deterioration rates using traffic count and pavement structural strength. Data were collected from the Talba-Mandela road in Minna, Niger State Nigeria, over 14 weeks including weekly measurements of pothole volume, traffic counts and pavement structural numbers. A multiple linear regression model was calibrated, achieving a 𝑅² of 80.8%. Validation indicated less than 10% deviation between observed and predicted data. These findings provide a data-driven approach to optimizing pavement maintenance schedules, reducing costs, and improving road durability.