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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| Format: | Article |
| Language: | English |
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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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| author | Ran Zhang Pengkun Hu Yuhui Zhong Long Wen Jie Ji Long Liang |
| author_facet | Ran Zhang Pengkun Hu Yuhui Zhong Long Wen Jie Ji Long Liang |
| author_sort | Ran Zhang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-2fbea3e84933417d8bb4105abfe69dc2 |
| institution | Kabale University |
| issn | 2095-7564 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Traffic and Transportation Engineering (English ed. Online) |
| spelling | doaj-art-2fbea3e84933417d8bb4105abfe69dc22025-08-20T03:38:48ZengKeAi Communications Co., Ltd.Journal of Traffic and Transportation Engineering (English ed. Online)2095-75642025-08-011241011103910.1016/j.jtte.2024.11.006Research progress on evaluation and prediction of degradation in service performance for asphalt pavementRan Zhang0Pengkun Hu1Yuhui Zhong2Long Wen3Jie Ji4Long Liang5School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China; Beijing Urban Transportation Infrastructure Engineering Technology Research Center, Beijing 100044, China; Corresponding author. School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaSchool of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaSchool of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaSchool of Civil Engineering, Tsinghua University, Beijing 100084, ChinaSchool of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China; Beijing Urban Transportation Infrastructure Engineering Technology Research Center, Beijing 100044, ChinaSchool of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaAsphalt 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.http://www.sciencedirect.com/science/article/pii/S2095756425001187Asphalt pavementService performanceDegeneration trendPrediction modelMachine learningFuture prospects |
| spellingShingle | Ran Zhang Pengkun Hu Yuhui Zhong Long Wen Jie Ji Long Liang Research progress on evaluation and prediction of degradation in service performance for asphalt pavement Journal of Traffic and Transportation Engineering (English ed. Online) Asphalt pavement Service performance Degeneration trend Prediction model Machine learning Future prospects |
| title | Research progress on evaluation and prediction of degradation in service performance for asphalt pavement |
| title_full | Research progress on evaluation and prediction of degradation in service performance for asphalt pavement |
| title_fullStr | Research progress on evaluation and prediction of degradation in service performance for asphalt pavement |
| title_full_unstemmed | Research progress on evaluation and prediction of degradation in service performance for asphalt pavement |
| title_short | Research progress on evaluation and prediction of degradation in service performance for asphalt pavement |
| title_sort | research progress on evaluation and prediction of degradation in service performance for asphalt pavement |
| topic | Asphalt pavement Service performance Degeneration trend Prediction model Machine learning Future prospects |
| url | http://www.sciencedirect.com/science/article/pii/S2095756425001187 |
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