A DEVELOPMENT OF FUZZY PAVEMENT CONDITION ASSESSMENT

Abstract

The pavement condition assessment (PCA) based on fuzzy set theory is presented. A method to determine membership functions used in PCA is proposed. The effects of inclusion or omission, weight changes and linguistic rating terms' range values changes of pavement parameters on PCA using fuzzy weighted average (FWA) operation are analyzed. The proposed method is compared with the MCI model. In developing this case, it is found that the proposed method gives more reliable results. Inclusion or omission, weight changes and linguistic rating terms' range values changes of pavement parameters can cause the differences in PCA. The recommendations with respect to PCA using FWA operation are given.