Abstract

Pavement rehabilitation is one of the most critical and costly forms of infrastructure asset management. Yet determining the subsequent performance of rehabilitated pavements is a complex task, particularly when multiple performance measures such as roughness, surface deformation, and structural integrity are considered. The complexity arises in part because of the interrelation among these performance measures and the fact that data relating to factors known to affect these measures may not be available. This paper seeks to demonstrate an appropriate methodological approach for studying the postrehabilitation performance of pavements using data from rural interstate roads in Indiana. Specifically, a random parameters seemingly unrelated equations approach is applied to explicitly account for the cross-equation correlation that exists among pavement-performance measures and the underlying heterogeneity across observations caused by imperfect data. The results provide some new insights into the interrelationships among the pavement rehabilitation treatments considered, pavement performance, traffic loads and trucks, weather and soil conditions, and rehabilitation expenditures.

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