The assessment of the road roughness conditions plays an important role to ensure the required performances related to road safety and ride comfort, furthermore providing a tool for pavement maintenance and rehabilitation planning. In this work, the authors compared the roughness index (International Roughness Index, IRI) derived from high speed inertial profilometer with two other roughness indices, one dynamic and one geometric computed on a digital elevation model (DEM) built by using mobile laser scanner (MLS) data. The MLS data were acquired on an extra-urban road section and interpolated on the nodes of a DEM with a curvilinear abscissa, coinciding with the global navigation satellite system (GNSS) track of the profilometer. To estimate the grid cell elevation, we applied two interpolation methods, ordinary kriging (OK) and inverse distance weighting (IDW), over the same data. The roughness values computed on the surface of the DEM showed a similar trend and a high correlation with those acquired by the profilometer, higher for the dynamic index than for the geometric index. The differences between the IRI values by profilometer and those computed on the DEM were small enough not to significantly affect the judgments on the analyzed sections. Moreover, the road sub-sections derived from profilometer measure that were classified as critical coincided with those derived from light detection and ranging (LiDAR) surveys. The proposed method can be used to perform a network-level analysis. In addition, to evaluate the effects of vibrations on human comfort, we input the DEMs into a dynamic simulation software in order to compute the vertical accelerations, as specified in the UNI ISO 2631 standard. The values obtained were in line and correlated with those inferred from the standard methodology for profilometer measures.
Concrete bridge inspection is nowadays primarily a slow, subjective, non-comprehensive and costly set of procedures. Automation of the acquisition method is especially desirable for economical and repeatability reasons. Digital data is normally derived from well established non-destructive testing techniques, high resolution cameras and, more recently, by 3D laser scanning. This latter technique has some advantageous aspects in terms of reliability, repeatability, completeness and intuitiveness of the analysis of the resulting 3D reconstruction of the concrete structure. Statical laser scanning is, though, impractical for a variety of different reasons. A possible way of overcoming such difficulties is represented by dynamical measurement, achieved by moving in a prescribed manner the laser scanner during the scanning process. This procedure, on the other hand, requires a reliable tracking system for the laser scanner position and orientation. This work focuses on the development of such system, based primarily on computer vision measurement systems. A compact and lightweight 3D laser scanner has been placed on an automated carrier able to move along a standard inspection by-bridge, and a system of cameras and transducers has been designed to measure the carrier position and orientation based on the assumption of rigid body motion of the by-bridge multi-link arm during inspection operations. Several experimental tests have been performed to assess the viability of the proposed system and to evaluate its performance.
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