Funding source: US DOT

Contract number: 69A3551747109

Funding amount: $28,183

Performance period: 7/1/2021 to 12/31/2023

Final Report: https://doi.org/10.25554/9hxw-3y87

The transportation infrastructure in Hawaii is vulnerable to natural hazards such as sea-level rise (SLR) and flash flooding. An urgent demand exists for rapidly monitoring roadway conditions and assessing post-hazard damage to repair and restore roads. Mobile LiDAR (Light Detection and Ranging) system (MLS) and mobile camera system (MCS) are two emerging technologies for mapping roadways. However, each technology has advantages and drawbacks: MLS can collect accurate 3D point clouds, but the system is not cost-effective for monitoring road conditions; on the other hand, MCS costs much less and is easy to operate, but it lacks sufficient geolocation accuracy. Currently, Hawaii Department of Transportation (HDOT) has been collecting MLS point clouds over all state roads once per year, but mainly for regular maintenance of roadways instead of for rapid response to natural hazards. The main goal of this project is to test the feasibility of combining the merits of MCS and MLS so that we can assess post-hazard road damage timely and accurately yet with a low operation budget. Our research involves several key components: 1) set up a low-cost MCS with panorama cameras to collect photos, 2) leverage the existing HDOT MLS point clouds to generate accurate georeferenced Digital Terrain Model (DTM) and orthomosaics from MCS data, and 3) develop innovative methods to map road damages (such as cracks and potholes) from the georeferenced MCS orthomosaics. Overall, this pilot study will develop a cost-effective solution to provide timely and accurate information about road damage and pave the way of incorporating state-of-the-art mobile mapping technologies for transportation-related hazard analysis.