Pavement Service Life Estimation and Condition Prediction
Cox Proportional Hazard Model and Linear Mixed Effects Model
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Remaining service life estimation and pavement condition prediction are two essential functions of Pavement Management Systems. This book first introduces the development of the Cox Proportional Hazards model for analysis on pavement remaining severice life. By specifying pavement condition rating (PCR) of 70 as the terminal pavement status, survival curves were developed based on historical PCR data using Cox Proportional Hazards method. Further, the estimated service lives of pavements were obtained from these survival curves. Results indicate the survival curve derived from the Cox model ca...
Remaining service life estimation and pavement condition prediction are two essential functions of Pavement Management Systems. This book first introduces the development of the Cox Proportional Hazards model for analysis on pavement remaining severice life. By specifying pavement condition rating (PCR) of 70 as the terminal pavement status, survival curves were developed based on historical PCR data using Cox Proportional Hazards method. Further, the estimated service lives of pavements were obtained from these survival curves. Results indicate the survival curve derived from the Cox model can be used to assist in pavement rehabilitation decision-making, overlay design, and budget allocation. Secondly, a linear mixed effects model (LMEM) is developed to predict the pavement condition for individual pavements. an example is given. Since LMEM uses a weighted combination of the deterioration trends of the family average and that of the specific pavement, it can significantly improve the prediction accuracy and can be used for project level pavement condition prediction.
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