Feasible treatment selection for routine maintenance of flexible pavement sing fuzzy logic expert system

Abstract

Pavement maintenance management system motivates to provide a scientific tool for maintenance and rehabilitation of roads pavement at desired serviceability levels. In view of the fund’s constraints and the need for judicious spending of available resources, the maintenance planning and budgeting are required to be done based on scientific methods. Unfortunately, the current maintenance practices are ad-hoc and subjective in nature. Pavement condition responsive maintenance is very useful for judicious disbursement of maintenance funds. The objective of this paper is to select a feasible treatment for routine maintenance based on pavement condition parameters of flexible pavement using Fuzzy Logic Expert System (FLES). Six different national highways have been selected to provide the maintenance based on the PCI, traffic volume, pavement age, precipitation, temperature and budget. FLES offers a convenient tool to better represent the uncertainty involved in pavement condition rating and assessment. The pavement maintenance treatment needs are generally determined based on the results of visual inspection, which in most of the cases does not give an adequate representation of pavement condition. Treatment selection FLES model has considered anticipated distresses-based condition index, anticipated traffic, and prevailing climate, age of the pavement and budget for treatments. Model predicts treatment types based upon their expected life. The triangular membership function for all the parameter is considered and analyzed with sufficient number of fuzzy rules as suggested by the maintenance engineers. The predicted result was compared with the twenty-five maintenance engineer’s responses, which shows homological results. Hence, this approach may provide an appropriate and economically viable maintenance treatment.