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This dataset contains pavement roughness and rut depth measured on provincial highways, summarized in 50 metre segments within the lane that the measure was taken.

This dataset contains pavement roughness and rut depth measured on provincial highways, summarized in 50 metre segments within the lane that the measure was taken.

The rutting dataset comprises of the annual rutting for years 2010-2020 (millimetre, calculated as the difference between current and previous year's data), with rut depth measurement from the previous year (millimetre), annual average daily traffic (AADT), lane width (metre), bearing capacity for year 2021 (tonnes), surface curvature index for year 2021, and base curvature index data (2021). The rutting data was collected for 20-metre road segments at specific latitude and longitude locations. The rutting is assumed to be linearly related to known explanatory variables (e.g., lane width) and random and spatial components. Rutting measurements were used to fit spatial-statistical models with random and spatial components in a Bayesian Hierarchical framework. Non spatial-statistical models with random yearly effects were also fitted. We compared these models to determine the importance of accounting for spatial information and to properly account for the rutting variability.

Terramechanical instruments were applied at newly assigned machine operating trails, in broadleaved-dominated mixed stands on cambisols in Lower Saxony, Germany. Afterward, a regularly planned cut-to-length thinning-operation was conducted. Measuring results were correlated with observed rut depth, resulting from the operating machines. Post-operational soil properties were quantified.

How to select suitable pavement materials for asphalt pavements according to the functional requirements of layers is still the focus of research by scholars in various countries. However, their effectiveness in combating high-temperature rutting and fatigue cracking in middle and lower layers is limited. To address this issue, a study optimized the incorporation of basalt fibers in different layers to improve road performance based on design specifications. Nine asphalt pavement structures with varying amounts of basalt fibers were assessed using an orthogonal test method. The optimal structure was determined considering factors such as fatigue life and overloading using the finite element method for modeling. Results showed that fiber dosage had a minimal impact on road surface bending subsidence and the location of tensile strain in the lower layer. Shear stresses were concentrated mainly at the outer edges of loads. Optimal dosages of basalt fiber were determined for different layers: 0.3% for the upper layer, 0.1% for the middle layer, and 0.3% for the lower layer. The optimal structure consists of a strong base with a thin-surfaced semi-rigid base layer, with 0.3% for the upper layer and 0.1% for the middle layer. This study provided valuable insights into designing basalt fiber asphalt pavement structures.