Using Belief Function Theory to Assist Pavement Maintenance and Rehabilitation Activities

Abstract

Abstract Several information technology approaches have been applied to life cycle analyses to improve decision-making performance and prolong infrastructure life spans. Belief function theory (BFT), also known as the Dempster-Shafer theory of evidence, is a method of representing uncertain, incomplete, and imprecise evidence of a system’s knowledge base. BFT has rarely been applied to pavement management until now. For pavement management decision-making, pavement engineers must formulate relationships between various objectives, incorporate subjective judgment, and pool evidence from various sources. These issues are not adequately addressed in the existing analytical tools used in pavement management. This paper conducts a study of pavement maintenance and rehabilitation (M&R) activities using BFT. Questionnaires are carried out to establish an evidential tree, which is used to quantify the level of uncertainty associated with M&R activities. With respect to the given evidence in the case study, the belief interval of (0.222, 0.778) with uncertainty for the M&R activities can be obtained by using Dempster’s rule of combination. BFT provides a more rigorous but straightforward approach to assisting pavement engineers with M&R decision-making.