Pavement Deterioration Modeling of the International Roughness Index Based on Fuzzy Logic Approach
The maintenance and rehabilitation of flexible pavements are crucial for achieving optimal performance and ensuring higher quality, enabling transportation planners to promptly formulate economically viable and sustainable pavement maintenance and rehabilitation strategies. Employing the fuzzy logic...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Pouyan Press
2025-07-01
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| Series: | Journal of Soft Computing in Civil Engineering |
| Subjects: | |
| Online Access: | https://www.jsoftcivil.com/article_202324_f2fce2afa9c7bac2141ec9f84137235e.pdf |
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| Summary: | The maintenance and rehabilitation of flexible pavements are crucial for achieving optimal performance and ensuring higher quality, enabling transportation planners to promptly formulate economically viable and sustainable pavement maintenance and rehabilitation strategies. Employing the fuzzy logic technique constitutes a productive methodology for assessing the degradation of flexible pavement. The fuzzy technique offers a convenient instrument for integrating subjective analysis uncertainty within the International Roughness Index (IRI) and evaluating maintenance requirements. This paper strives to construct a system rooted in fuzzy logic to appraise the requirements for maintenance and (IRI) evaluation within a network of pavement roads. This system utilizes data on pavement distress collected from the United States and Canada to achieve its objectives. Various types of pavement distress, such as fatigue cracking, rutting, longitudinal cracking, block cracking, transverse cracking, patching, ravelling, and potholes, are input variables; these parameters are fuzzified into fuzzy subsets with triangular membership functions. The performance evaluation of the analytical models was conducted using several performance indicator metrics, including the coefficient of determination (R2), root mean squared error (RMSE), and mean absolute error (MAE). |
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| ISSN: | 2588-2872 |