Building information modeling (BIM) is a process that has shown great potential in the building industry, but it has not reached the same level of maturity for transportation infrastructure. There is a standardization need for information exchange and management processes in the infrastructure that integrates BIM and Geographic Information Systems (GIS). Currently, the Industry Foundation Classes standard has harmonized different infrastructures under the Industry Foundation Classes (IFC) 4.3 release. Furthermore, the usage of remote sensing technologies such as laser scanning for infrastructure monitoring is becoming more common. This paper presents a semi-automated framework that takes as input a raw point cloud from a mobile mapping system, and outputs an IFC-compliant file that models the alignment and the centreline of each road lane in a highway road. The point cloud processing methodology is validated for two of its key steps, namely road marking processing and alignment and road line extraction, and a UML diagram is designed for the definition of the alignment entity from the point cloud data.

Monitoring and digitalization are key to improve the resilience of the infrastructure network in the context of assessing its disaster management cycle. SAFEWAY is a project funded by the H2020 framework that aims to assess infrastructure resilience integrating multiscale information attending to all modes of disaster management cycle. This work presents the methodologies developed in the project for road and rail infrastructure monitoring and modelling, using remotely sensed data from Mobile Mapping Systems (MMS). First, 3D point clouds of both road and rail infrastructure are heuristically processed, obtaining geometric and semantic information from the most relevant assets, as well as the alignment, which is a key entity for generating information models. Such models are computed following the specifications of the Industry Foundation Classes (IFC) 4.1 schema, considering its current limitations and future potential for linear infrastructure modelling. Finally, the information is centralized in a core software platform where a user interface has been developed to aid visualization and interpretation of the resulting data.