Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Application of Mobile Terrestrial LiDAR Scanning Systems for Identification of Potential Pavement Rutting Locations
Ist Teil von
Transportation research record, 2021-09, Vol.2675 (9), p.1063-1075
Ort / Verlag
Los Angeles, CA: SAGE Publications
Erscheinungsjahr
2021
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
Periodic measurement and identification of the presence and severity of pavement rutting are crucial for pavement management programs conducted by state transportation agencies. This paper proposes a novel analytical method for identifying pavement rutting locations using data collected by mobile terrestrial LiDAR scanning (MTLS). Four vendor MTLS systems were evaluated based on their ability to accurately reproduce a roadway’s transverse profile. To establish ground-truth measurements, 2 in. interval pavement transverse profiles, which included rutting sections, were collected using traditional surveying techniques. MTLS transverse profiles were evaluated using partial curve mapping, Fréchet distance, area, curve length, and dynamic time warping techniques. Resultant pavement transverse profiles were compared between vendors and a profile created from traditional surveying. Results indicate that calibrated MTLS systems can provide accurate transverse profiles for potential identification of pavement rut areas. Based on this determination, a novel method was developed for use in identifying locations of pavement rutting through analysis of the curvature of MTLS raster surfaces. After evaluating three grid cell sizes for elevation raster surfaces, a raster grid cell size of 1 ft × 1 ft was determined to be most suitable for identifying continuous concave raster cell groups along wheel path trajectories. These cell groupings were found to reliably identify pavement rutting locations. The analytical procedures employed through application of this method consist of an efficient workflow process that is not reliant on a time-consuming continuous comparison with an MTLS-modeled uniform surface.