Suliman Gargouma, Karim El-Basyounya
Light Detection and Ranging (LiDAR) scanning systems integrate laser scanners, Global Positioning Systems, and inertial navigation technologies into one system that can acquire positional data and intensity information about surrounding objects. In Mobile Laser Scanning, data collection equipment is mounted on a truck that travels through a highway creating a 3D point cloud image of the entire road segment. The high point density of such datasets enables automated extraction of multiple roadway features, which are typically collected manually during long site visits. In addition, LiDAR datasets could also be used to assess geometric elements of highways such as available stopping sight distance. If used to their full potential, LiDAR datasets could create a paradigm shift in how geometric assessments and safety audits on highways are conducted. To highlight the full potential of LiDAR data in transportation engineering and to address doubts about the feasibility of extracting information from LiDAR, this research effort provides a thorough review existing and future applications in this area. Unlike previous research, this effort includes a thorough review of the previous attempts of data extraction from LiDAR while highlighting limitations in existing algorithms and areas where more research is required.
Transportation Engineering; Highway Design; Infrastructure Management; LiDAR; Remote Sensing