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Building durable and sustainable pavements
| Content Provider | Scilit |
|---|---|
| Author | Al-Qadi, Imad L. Qiao, Yu Chen, Sikai Alinizzi, Majed Labi, Samuel |
| Copyright Year | 2018 |
| Description | A key aspect of pavement management systems is the need for reliable pavement condition data because this data are used to assess pavement network condition, to schedule Maintenance and Rehabilitation (M&R), and to estimate the level of funding needed for M&R. Poor quality of data leads to misclassification of the pavement condition, mistiming of M&R investments, inaccurate reporting of the effectiveness of individual projects or systemwide programs, and ultimately, wasteful spending of agency budgets or user frustration due to unduly deferred maintenance. Reporting pavement condition for a wide variety distress indicators across the entire carriageway and over several miles means that massive amount of data need to be collected. This study developed Gaussian-distribution regression models that captured the relationship between pavement indicators. The developed models could use a single indicator to predict the occurrence or severity of other indicators, which could help reduce data collection and processing efforts. Book Name: Advances in Materials and Pavement Performance Prediction |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2018-0-84692-8&isbn=9780429457791&doi=10.1201/9780429457791-2&format=pdf |
| Ending Page | 3 |
| Page Count | 1 |
| Starting Page | 3 |
| DOI | 10.1201/9780429457791-2 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2018-07-16 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Advances in Materials and Pavement Performance Prediction Transportation Pavement Condition Developed Gaussian Developed Models |
| Content Type | Text |
| Resource Type | Chapter |
