3D POINT CLOUD TO BIM: AUTOMATED APPLICATION TO DEFINE IFC ALIGNMENT AND ROADWAY WIDTH ENTITIES FROM MLS-ACQUIRED LiDAR DATA OF MOUNTAIN ROADS

Abstract

Abstract. The growing trend of developing standards of information exchange and management processes is leading to Building Information Models (BIM) being adapted to work with linear infrastructure assets. For this reason, the Industry Foundation Classes (IFC) has developed standards for linear infrastructure such as roads. Furthermore, the usage of remote sensing technologies, such as Mobile Laser Scanning (MLS) systems for infrastructure monitoring is increasingly common. This paper presents an automated methodology that takes as input 3D point cloud tiles from an MLS and its trajectory, and outputs an IFC-compliant file that models the alignment of the road and the width of the roadway along the length of the road. The methodology is evaluated in 48 km of mountain roads, in some cases without road markings, using neither intensity nor colour fields.

Civil Integrated Management (CIM) for Advanced Level Applications to Transportation Infrastructure: A State-of-the-Art Review

“…The possibility of settlement, which is a maintenance condition evaluation item for fill-dam bodies, was investigated using point clouds based on the Unmanned Aerial System (UAS) from motion and terrestrial laser scanner point clouds [19]. An automated technique employed 3D point cloud tiles with trajectory points to construct Industry Foundation Class (IFC) models of roadways and determine their alignment and width [92].…”

Vectorizing urban road markings from mobile laser scanning point clouds

“…MLS point clouds are unstructured and heavy data. Because of the lack of pre-existing spatial indexation, and to reduce computational burden, point clouds are very often cut in smaller overlapping areas [2,3]. To further reduce the volume of data to process, most of the processing chains performs a ground/non-ground segmentation.…”