Development of framework for performance prediction of flexible road pavement in Nigeria using Fuzzy logic theory

Though several attempts have been made in the past to develop performance prediction models for flexible road pavement in Nigeria, insufficient dataset remained the major problem of using such models. This study used Fuzzy logic theory which is capable of handling the challenge of imprecise dataset to develop a framework for performance prediction of flexible road pavement in Nigeria. A Fuzzy Inference System was developed using MATLAB software. The attributes used included; Initial Pavement Surface Condition, Age of pavement, Resilient Modulus of subgrade soil, Average Truck load per day, Average Annual Air Temperature and Rainfall to predict the Future Pavement Surface Condition (FPSC). The model was calibrated using observed logical behaviour of pavement to fit engineering experience and judgement. A goodness-of-fit test showed high level of accuracy at 81.63% which was validated at 74.13% using extrapolated dataset of the same source. The study proposed 5120 mutually exclusive decision rules for performance prediction of flexible road pavement based on permutation theory. Though there was no current and well-spread dataset that described the present pavement condition to calibrate the decision rules, a framework for performance prediction of flexible road pavement using Fuzzy logic theory was developed for pavement engineers in Nigeria.