MPC Research Advances Automated Data Collection on Roadway Assets
Posted: Nov 18, 2022
Researchers at the University of Utah are studying automated data collection technologies that can be used to gather information on roadway assets such as traffic signs, bridges, pedestrian access ramps, and pavement. Their research confirms that LiDAR technology is currently best suited for the in-motion collection of data on roadway assets but does not provide enough detail for remote structural bridge inspections. Image-based 3D reconstruction is an accurate solution for remote inspection of pedestrian access ramps. Mobile photogrammetry shows promise for assessing pavement condition. Consequently, this research will help agencies choose asset data collection technology that best meets their needs and will provide future direction for further refining automated roadway asset data collection technologies.
Researchers at the University of Utah are studying automated data collection technologies that can be used to gather information on roadway assets such as traffic signs, bridges, pedestrian access ramps, and pavement. Their research confirms that LiDAR technology is currently best suited for the in-motion collection of data on roadway assets but does not provide enough detail for remote structural bridge inspections. Image-based 3D reconstruction is an accurate solution for remote inspection of pedestrian access ramps. Mobile photogrammetry shows promise for assessing pavement condition. Consequently, this research will help agencies choose asset data collection technology that best meets their needs and will provide future direction for further refining automated roadway asset data collection technologies.