Title: "Development of Pavement Prediction Models Using Markov Chain Theory for Egyptian Highway Network"
         

DOI: 10.15224/978-1-63248-065-1-44
Page(s): 61 - 66
Authors: HESHAM ABDELKHALEK, SHERIF HAFEZ, SHERIF ELTAHAN, WAEL BEKHET

Abstract

Typically, available funds are not adequate to satisfy all the required improvement, repair and/or maintenance projects for the highways and roads networks in most countries, including Egypt. Under current policies and funding levels, further deterioration in the highways can be expected, since the budget needed for highway maintenance is greater that the funding levels available. As a result, highway agencies must seek more cost-effective methods for highway network preservation. Pavement performance prediction models are generally used to forecast changes in condition over some future time period. Predicted conditions are used in several pavement management activities. Markov chain theory has been used in this paper to develop future pavement deterioration prediction model for highways in Egypt, and to forecast the future pavement performance. Transition Probability Matrices (TPM) were generated for two highways in Egypt as a case study; namely, the Alexandria-Cairo Agricultural R and the Alexandria-Matrouh North Coast Highway. TPMs were developed based on data made available through the Central Administration for Road Maintenance, at the General Authority for Roads and Bridges and Land Transport (GARBLT). The Pavement Condition Index (PCI) was used as pavement performance indicator. The pavement deterioration prediction model were developed for the two highways consider in the case study for a planning horizon of five years. The results of the models were then validated using actual data outside the planning horizon and the difference between the predicted data and validation data was insignificant at a 95% confidence level.