Fuzzy expert system for asphalt pavement performance prediction

Presents an expert system based on fuzzy logic to predict the rut depth of asphalt pavements, given the parameters of construction materials, pavement thickness, road age and traffic count. A GUI in Visual BASIC was built, which invokes the fuzzy inference engine when submitted with the required input data. The result obtained is sent to the GUI window as rut depth. The aim is to be able to determine the pavement condition after a certain time period, given the pavement construction materials, the age and the traffic to which the pavement is/will be exposed. The long-term pavement performance (LTPP) database is made use of in this paper. The data extracted from this database is used in the designing and testing of the fuzzy inference system. The membership functions of all the input parameters are built in accordance with these database records. The rules defining the behavior of the fuzzy inference system are written by taking into account the data available as well as by using logical reasoning. The resulting system can predict possible rut depths till 15 years since construction. A correlation of 0.700829 was obtained between the measured readings available in the data and the output obtained by the fuzzy inference system. The regression analysis done on the data gave an R square factor of 0.92 and higher for the fuzzy model and 0.78 and lower for the actual data. This indicates that the fuzzy expert system gave a much better estimate of the prediction of the performance of pavement than the original data.