2 resultados para Superficial roughness

em Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States


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The Iowa Department of Transportation has been determining a present serviceability index (PSI) on the primary highway system since 1968. A CHLOE profilometer has been used as the standard for calibrating the Roadmeters that do the system survey. The current Roadmeter, an IJK Iowa DOT developed unit, is not considered an acceptable Roadmeter for determining the FHWA required International Roughness Index (IRI). Iowa purchased a commercial version of the South Dakota type profile (SD Unit) to obtain IRI. This study was undertaken to correlate the IRI to the IJK Roadmeter and retire the Roadmeter. One hundred forty-seven pavement management sections (IPMS) were tested in June and July 1991 with both units. Correlation coefficients and standard error of estimates were: r' Std. Error PCC pavements 0.81 0.15 Composite pavements 0.71 0.18 ACC pavements 0.77 0.17 The correlation equations developed from this work will allow use of the IRI to predict the IJK Roadmeter response with sufficient accuracy. Trend analysis should also not be affected.

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This report describes a short-term study undertaken to investigate the potential for using dense three-dimensional (3D) point clouds generated from light detection and ranging (LIDAR) and photogrammetry to assess roadway roughness. Spatially continuous roughness maps have potential for the identification of localized roughness features, which would be a significant improvement over traditional profiling methods. This report specifically illustrates the use of terrestrial laser scanning (TLS) and photogrammetry using a process known as structure from motion (SFM) to acquire point clouds and illustrates the use of these point clouds in evaluating road roughness. Five roadway sections were chosen for scanning and testing: three gravel road sections, one portland cement concrete (PCC) section, and one asphalt concrete (AC) section. To compare clouds obtained from terrestrial laser scanning and photogrammetry, the coordinates of the clouds for the same section on the same date were matched using open source computer code. The research indicates that the technologies described are very promising for evaluating road roughness. The major advantage of both technologies is the large amount of data collected, which allows the evaluation of the full surface. Additional research is needed to further develop the use of dense 3D point clouds for roadway assessment.