Fuzzy Representation of Pavement Condition for Efficient Pavement Management

Abstract: Many government agencies and private consulting companies manage large pavement networks in terms of infrastructure condition assessment and maintenance planning. Efficient pavement management is supported by pavement management systems (PMSs), which includes models for pavement condition assessments considered “valuable” by agency's engineers. The objective of this article is to define a pavement condition model able to overcome surveyors’ subjectivity in rating distresses and thus provide meaningful pavement conditions for the agencies to employ in project planning. The article proposes a fuzzy inference model for calculating pavement condition ratio (PCR) specifically tailored on the Alabama Department of Transportation Pavement (ALDOT) guidelines and policies. Applied to several surveyors’ ratings, the proposed model has the ability to smooth distress extent differences among surveyors producing PCR values within acceptable range of variability. The proposed approach has the intention of not only enhancing pavement condition characterization but also to exploit the opportunity made available by automation in the collection and interpretation of pavement data which are anyway characterized by an inherent subjectivity.