Automated Lidar Data to Develop and Manage Active Transportation Asset Inventories
Pedestrian crosswalks, bike lanes, and medians are key safety devices in a multi-modal highway network. However, there is no statewide map of these assets' locations and types. Such a map would benefit planning, maintenance, safety assessments, and network analyses for ODOT and its partners. Currently, ODOT collects asset information through site visits and surveys, which are labor-intensive and costly across the state's vast road network. GIS databases are created ad-hoc and inconsistently, often by interns. Fortunately, ODOT Engineering Automation regularly collects 3D mobile lidar data, providing geometric and radiometric information. This research reviewed state-of-the-art approaches for detecting and classifying pedestrian crosswalks, bike lanes, and medians, and developed a methodology to extract these features from LiDAR datasets for updating ODOT’s GIS platform. The approach was tested on several datasets and showed good extraction performance, requiring minimal manual cleanup. Lastly, a plan is provided for ODOT to implement this research.
Infrastructure Assets: Highway Assets, Other Highway Assets
Resource Types: Research Report
Capabilities: Tools & Technology
Management Processes: Performance Based Planning & Programming