Project Details
RESEARCHERS
Hongbin Xu, Moo Yeon Kim, Christian Sabilon, Lu Gao, Jorge A Prozzi
KEYWORDS
Calibration, Data analysis, Deterioration, Forecasting, Maintenance management, Pavement management systems, Pavement performance, Rehabilitation (Maintenance)
Project description
Texas Department of Transportation's (TxDOT’s) Pavement Management Information System (PMIS) has been recently replaced by Pavement Analyst (PA), a system for archiving, managing, and mapping data, reporting performance prediction, conducting optimization analysis for decision-making, etc. Pavement performance models comprise a key component of PA, these models quantify pavement deterioration for the planned horizon and predict the effect of maintenance and rehabilitation actions on performance. The accurate prediction of pavement performance is important for efficient management of the transportation infrastructure. By reducing the prediction error of pavement deterioration, agencies can obtain significant savings through timely intervention and accurate planning. As part of this project, the authors reviewed the current performance models, calibrated them, and updated them in a manner compatible with their implementation into PA. Extensive data analysis was conducted by using traditional and advanced data analysis techniques. Specifically, the models developed addressed the following technical objectives: (1) existing models were calibrated, correcting for biases and inefficiencies, (2) models were updated to incorporate historical construction data, (3) models were updated to incorporate the effect of maintenance and rehabilitation activities, and (4) alternative models were proposed that are free of some of the limitations of the existing models but are simple and straightforward enough to incorporate into PA.