Empirical Analysis of Pavement Condition Transition Probabilities
Publication: Construction Research Congress 2024
ABSTRACT
Due to needs of maintaining pavements located in statewide, the “one size fits all” approach for estimating pavement conditions no longer works as pavement deterioration depends on roadways’ characteristics. Understanding how pavement deterioration probabilities vary based on diverse factors is critical to improve accuracy of pavement condition estimations. The objectives of this paper are to build empirical Markov Chain pavement deterioration models and analyze how transition probabilities of pavement condition differ depending on multiple factors. The data of the Georgia Department of Transportation pavement inspection records from 2017 to 2021 is used to develop Markov Chain models and evaluate pavement condition transition probabilities. The major finding of this research is that pavement condition transition probabilities significantly vary depending on highway system types, traffic volume, and annual average temperature. It is anticipated that findings from this research will help highway agencies to improve accuracy of long-term forecasting of pavement performance.
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Construction Research Congress 2024
Pages: 751 - 758
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Published online: Mar 18, 2024
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