FLEXIBLE PAVEMENT DISTRESS PREDICTION MODEL FOR THE CITY OF RIYADH, SAUDI ARABIA

The Pavement Maintenance Management System (PMMS) of Riyadh city performs comprehensive pavement visual survey prior to each maintenance program. In the condition survey, detailed information related to type, severity and density of existing distresses is collected. The collected data is then used to determine needed maintenance activities on the network and a project level. This process was proven to be costly and very time consuming. The objective of this paper is to develop distress prediction models. The model cover all common types of distress exist on Riyadh’s street network. The model predicts distress density over time associated with each severity level, pavement condition, traffic level and highway class combinations. The model developed for a total of 61 and 28 cases for main and secondary streets, respectively. All the developed models were found to be statistically significant in predicting distress density. The models were validated using reserved data points. The validation process indicated that the models can adequately predict the distres