A data-driven approach for gravel road maintenance

Gravel roads are important assets for geographically sparse countries, but the maintenance of these roads is costly and inefficient. In addition, as failure development is highly affected by environmental factors, the planning should be dynamic for reaching efficiency and effectiveness, which is achieved by data-driven maintenance approaches. This paper proposes applying a data-driven approach in gravel road maintenance following the steps of the OSA-CBM specifications. The conceptual approach is developed and illustrated based on the findings of an extensive literature review. The approach thus contextualises OSA-CBM in gravel road maintenance and points out further development and research areas. It was found that the research has mainly focused on data acquisition techniques, road condition classification, diagnostics, and deterioration models, while data manipulation methods and prognostic models for gravel roads are rather unresearched areas. In addition, a holistic approach towards data-driven maintenance of gravel roads is currently lacking. In this perspective, the approach presented in this paper could serve as a base for the further development of data-driven methods to reach efficient and effective gravel road maintenance practices.