Evaluation of the existing performance models used for pavement management by the Texas Department of Transportation

Abstract

The pavement management information system (PMIS) and hics. the flexible pavement design software, FPS-19, used by the Texas Department of Transportation (TxDOT) for pavement management at network and project level respectively, generally do not give the same answer when the same set of data are used. This thesis is a part of the study to develop an approach for integrating pavement management systems at the two levels. The objective of the study is to identify which performance models were working satisfactorily and which needed to be modified. The performance models for ride quality (serviceability index for FPS-19), shallow rutting, deep rutting, and alligator cracking, which are the fundamental performance measures of the flexible pavements, were selected for evaluation. From the family of flexible pavements, the newly constructed pavements with untreated base were considered in the evaluation. A sensitivity analysis was performed to determine the relative importance of the input variables to FPS-I9 program. To reduce the number of problems to a manageable size, a one factor at a time approach was used. The F-statistics corresponding to the relevant input variables were used to determine the ranks. It was found that reliability level is the most important factor in FPS-19, followed by twenty-year projected axle repetition (ESAL). A research database was created by extracting data from the Long Term Pavement Performance (LTPP) database for pavement sections in Texas. A11 data items except rutting data were extracted using the software, Database 97. Rutting data was obtained from the LTPP regional office. Data from sixteen pavement sections were available for the evaluation. Elastic moduli of pavement layers and subgrades were back-calculated using MODULUS software. The selected performance models were evaluated using trend analyses, statistical hypotheses tests, percent difference, and estimated reliability. Due to the lack of data, all members of the performance model families could not be checked. It was observed that none of the selected performance models of PMIS and FPS-I9 is predicting the values observed at the LTPP sites though some of them are predicting better than others. Therefore, improvements are recommended for all the evaluated performance models.