Cumulative Distribution-Based Method for Pavement Performance Modeling

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Abstract Pavement performance prediction is the basis for maintenance decisions. Predicting future pavement conditions accurately and efficiently helps determine the optimal maintenance time, select appropriate measures, and allocate rehabilitation funds effectively. However, limited to the instability and variability in pavement condition data collection, deterministic models are not always reliable for all pavement situations. On the other hand, probabilistic-based models are influenced by environmental factors that are challenging to quantify. Recognizing the limitations of the above two methods, this paper proposes a cumulative distribution-based technique for developing pavement performance prediction models. First, after comparing performance metrics such as pile-by-pile single-point, probability density, and cumulative distribution, it is evident that the cumulative distribution is the most reliable method for describing pavement conditions. A continuous distribution function is created from a limited set of discrete observed field pavement condition data using the sampling theorem. With cumulative distribution-based deterioration curves changing over time, it is possible to predict future pavement deterioration rates. A case study is presented at last. Analyses of the predicted curve and observed pavement performance indicate that the cumulative distribution-based technique is effective in modeling pavement performance and can provide reliable predictive results.

Key words： road engineering pavement performance prediction cumulative distribution Montecarlo simulation sampling theorem pavement management system

Received: 13 November 2023

Fund:This work was supported by 2022 Ningbo Transportation Science and Technology Plan Project (Grant No.202216).

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	Articles by authors
	TU Chen-hao
	YE Wen-ya
	ZHANG Rui
	QIAN Xu-dong
	YANG Qun

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TU Chen-hao,YE Wen-ya,ZHANG Rui, et al. Cumulative Distribution-Based Method for Pavement Performance Modeling[J]. Journal of Highway and Transportation Research and Development, 2024, 18(2): 14-25.

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http://journal10.magtechjournal.com/Jwk_gljtkj_en/EN/ OR http://journal10.magtechjournal.com/Jwk_gljtkj_en/EN/Y2024/V18/I2/14

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