Research progress on evaluation and prediction of degradation in service performance for asphalt pavement
Asphalt pavement is the main type of pavement structure in China, and it accounts for more than 90% of the large-scale road network. As the service life of asphalt pavement increases, the demand for maintenance is increasing significantly. Accurately revealing the degradation mechanism and predictin...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-08-01
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| Series: | Journal of Traffic and Transportation Engineering (English ed. Online) |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095756425001187 |
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| Summary: | Asphalt pavement is the main type of pavement structure in China, and it accounts for more than 90% of the large-scale road network. As the service life of asphalt pavement increases, the demand for maintenance is increasing significantly. Accurately revealing the degradation mechanism and predicting the performance of asphalt pavement is the basis for the scientific maintenance decisions. Meanwhile, it is also beneficial for road construction planning and resource allocation. Based on numerous current studies, this review firstly provides a comprehensive summary of the internal factors such as structure and material, as well as external factors such as environment, load, and construction, that impact the performance of asphalt pavement. Simultaneously, the degradation trend of asphalt pavement performance under intricate conditions is also clarified. Furthermore, the commonly used performance prediction models of asphalt pavement are analyzed, such as deterministic methods, uncertainty methods, machine learning, dynamic methods and so on. And their applicability and limitations are also summarized. Finally, considering the complexity of predicting asphalt pavement performance, this review identifies key challenges and future prospects in this area. This provides theoretical support for accurately predicting the performance degeneration of asphalt pavement, making scientific maintenance decisions, and promoting the durability improvement of asphalt pavement. |
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| ISSN: | 2095-7564 |