Implementation of the Structural Condition Index into the Louisiana Pavement Management System Based on Rolling Wheel Deflectometer Testing
Omar S. Elbagalati, Mostafa A. Elseifi, Kevin Gaspard, Zhongjie Zhang
Abstract
Omar S. Elbagalati, Mostafa A. Elseifi, Kevin Gaspard, Zhongjie Zhang
Abstract
Structural condition data are commonly collected at the project level with falling weight deflectometer measurements. However, recent developments in continuous deflection devices allow characterization of pavement structural conditions at the network level. This study introduces a framework for incorporating pavement structural conditions into the decision matrix of Louisiana’s pavement management system at the network level. The proposed framework fills the gap between network-level and project-level decisions, allowing more accurate budget estimation. In this study, rolling wheel deflectometer measurements were used to evaluate pavement structural conditions according to the structural condition index (SCI). Two enhanced decision trees, for collectors and arterials, were developed, such that both functional and structural pavement conditions are considered in the decision-making process. Implementation of the SCI in the decision-making process is demonstrated and is expected to improve the overall performance of the pavement network. Furthermore, the enhanced decision trees are expected to reduce the total maintenance and rehabilitation construction costs if applied to relatively high-volume roads (e.g., Interstate highways, arterials, and major collectors).
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Structural condition data are commonly collected at the project level with falling weight deflectometer measurements. However, recent developments in continuous deflection devices allow characterization of pavement structural conditions at the network level. This study introduces a framework for incorporating pavement structural conditions into the decision matrix of Louisiana’s pavement management system at the network level. The proposed framework fills the gap between network-level and project-level decisions, allowing more accurate budget estimation. In this study, rolling wheel deflectometer measurements were used to evaluate pavement structural conditions according to the structural condition index (SCI). Two enhanced decision trees, for collectors and arterials, were developed, such that both functional and structural pavement conditions are considered in the decision-making process. Implementation of the SCI in the decision-making process is demonstrated and is expected to improve the overall performance of the pavement network. Furthermore, the enhanced decision trees are expected to reduce the total maintenance and rehabilitation construction costs if applied to relatively high-volume roads (e.g., Interstate highways, arterials, and major collectors).
Key concepts: Falling weight deflectometer, Pavement management, Deflection (physics), Pavement engineering, Engineering, Driver rehabilitation, Structural health monitoring, Transport engineering