Abstract

Accurate prediction of performance decay law is an important basis for long-term planning of maintenance strategy. The statistical regression prediction model is the most widely employed method to calculate pavement performance due to its advantages such as the small amount of calculation and good accuracy, but the traditional prediction model seems not applicable to the high maintenance level areas with excellent pavement conditions. In this paper, the service life and the cumulative number of the axle load were determined as the independent variables of prediction models of pavement performance. The pavement condition index (PCI) and rutting depth index (RDI) were selected as maintenance decision control indexes to establish the unified prediction model of PCI and RDI respectively by applying the cosine deterioration equation. Results reveal that the deterioration law of PCI presents an anti-S type or concave type and the deterioration law of RDI shows an obvious concave type. The prediction model proposed in this study added the pavement maintenance standard factor d, which brings the model parameter α (reflecting the road life) and the deterioration equations are more applicable than the traditional standard equations. It is found that the fitting effects of PCI and RDI prediction models with different traffic grades are relatively similar to the actual service state of the pavements.

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