Abstract
Various studies have been recently conducted to predict pavement condition, but most of them were developed in a certain region where climate conditions were kept constant and/or the research focused on specific road distresses using single parameters. Thus, this research aimed at determining the influence of pavement structure, traffic demand, and climate factors on urban flexible pavement condition over time. To do this, the Structural Number was used as an indicator of the pavement capacity, various traffic and climate variables were defined, and the Pavement Condition Index was used as a surrogate measure of pavement condition. The analysis was focused on the calibration of regression models by using the K-Fold Cross Validation technique. As a result, for a given pavement age, pavement condition worsens as the Equivalent Single Axle Load and the Annual Average Height of Snow increased. Likewise, a cold Annual Average Temperature (5–15 °C) and a large Annual Average Range of Temperature (20–30 °C) encourage a more aggressive pavement deterioration process. By contrast, warm climates with low temperature variations, which are associated with low precipitation, lead to a longer pavement service life. Additionally, a new classification of climate zones was proposed on the basis of the weather influence on pavement deterioration.
Highlights
In order to better understand pavement condition evolution, this study aims at analyzing the combined influence of pavement capacity and climate and traffic conditions on pavement deterioration process based on the historic pavement data provided by the Long-Term Pavement Performance (LTPP) program [10]
This study considered road sections characterized by very different traffic and climate conditions, pa was able to represent the pavement deterioration proceTshsepmroapinerfalyc.toTrhine prealvaetmioennsthdipetbereitowraeteinonPpCroI caenssd, wpahiwchasismcoondseidleedredtharosutogchhaEsqtiucapthioenno(m2)enthoant, wdeasscrpiabveesmaelninteaagred(epcar).eaAslethoofuPgChIthovisesrtutidmye;coFnigsuidreer3edprlooatsdtsheectdioantas. cShpaercaicfitcearilzlye,dthbey PvCerIyodfiafferroeandt streacffitiocnadnedccrleiamseasteapcopnrodxitiimonaste, lpya 5wuansiatsblpeetroyreeaprrfersoemnttthheefpirasvt eymeaernatnddetaehriaolrfaotifointspcrooncsetsrsucptrioopn.erly
Unlike most previous studies on the analysis of pavement deterioration that were developed in a specific region or state and based on single parameters (IRI, cracking, or rutting), this research was carried out using urban pavements located in 17 states and considering the Pavement Condition Index (PCI), which better represents pavement deterioration than single parameters [7,16]
Summary
A poor or wrong maintenance strategy might cause a significant deterioration of this heritage [3]. For this reason, various highway agencies have developed Pavement Management Systems (PMS) to analyze the life cycle of existing road infrastructures by means of pavement deterioration models [4]. Various highway agencies have developed Pavement Management Systems (PMS) to analyze the life cycle of existing road infrastructures by means of pavement deterioration models [4] In this regard, many studies have been developed to identify which factors are affecting road deterioration over time [5,6]. Most of these studies were focused on the calibration of pavement deterioration models for interurban roads; their application to urban pavements might not be representative because significant differences exist between both types of pavements regarding road traffic, pavement structure, cross-section, and the influence of distresses on serviceability [7]
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