Transition Probability Matrices for Flexible Pavement Deterioration Models with Half-Year Cycle Time

Abstract

Pavement performance models, a vital part of pavement management systems and life-cycle analysis, are generally divided into deterministic and probabilistic ones. Among probabilistic models, the Markov chains are attracting great attention. Transition probability matrices were developed for flexible pavement road network of the Republic of Moldova using the IRI values collected twice a year, in spring and in autumn, from 2013 to 2015. Consequently, a half-year cycle time was established. The aim of this paper is to demonstrate that it is feasible to develop transition probability matrices for an entire flexible pavement network using data from a short data collection period, and simultaneously carrying out maintenance and rehabilitation activities, if some assumptions are made. Results showed that road sections can drop two or three states in one cycle time, not only remaining in the same state or evolving to the next one, as it is usually assumed in pavement performance modeling. These models are proposed for countries in similar circumstances; a network with no new roads constructed in last decades, pavements maintained or rehabilitated in different moments during their service life, invalid or useless pavement condition data from previous years and unknown pavement structure in most of the sections.