Implementation of Unmanned Aerial Vehicles (UAVs) for Assessment of Transportation Infrastructure – Phase II

For information concerning Phase I of project, click here.

Final report for Phase II of project, click here.

Through successful research, development, and demonstrations during Phase 1 of this project, the Michigan Tech team was able to test multiple sensors on a Michigan-made multirotor UAV platform, along with other UAVs, enabling the collection of data types such as optical, light detection and ranging (LiDAR), and thermal to achieve a detailed view of various MDOT infrastructure.

Further development of UAV technology for the use of transportation infrastructure assessment is required in order to fully implement these technologies into MDOT day-to-day operations. By successfully continuing UAV research and development for MDOT, the Michigan Tech team produced practical applications of large datasets that supports MDOT’s business models and decision making processes as part of this Phase II analysis.

The objectives of the Phase II research project were to develop, deploy, and implement:

UAV technology for the use of transportation infrastructure assessment was further developed to implement into MDOT day-to-day operations. Through this project, the team has successfully completed the following:

  1. Bridge deck and road corridors have been inspected using high-resolution optical, thermal, and LiDAR technologies. Algorithms have been created and updated to automatically identify and quantify defects such as spalls, delaminations, and cracks.
  2. Backhaul and data storage capabilities have been expanded upon to include a secure storage and a geospatial portal that has data “push” and “pull” capabilities.
  3. Detailed reporting describing and recommending methods for MDOT to store and distribute large UAV-collected datasets.
  4. Collected LiDAR data along a bridge and road corridor.
  5. Developed a traffic monitoring algorithm that uses imagery collected via a UAV platform.
    Monitored and modeled construction sites, including quantifying the volumetrics of gravel piles using optical sensors.
  6. Developed a benefits-costs analysis to determine MDOT’s return on investment that will result from deploying UAVs.
  7. Multiple team members have secured FAA Unmanned Remote Pilot Licenses.

Michigan Tech Project Team Members

Colin Brooks: Principal Investigator – Transportation infrastructure condition assessment

Thomas Oommen, PhD: Co-Investigator – Thermal imaging and analysis

Tim Havens, PhD: Co-Investigator – Light Detection and Ranging Analysis (LiDAR)

Tess Ahlborn, PhD: Co-Investigator – Civil engineering expertise for condition assessment

Kuilin Zhang, PhD: Co-Investigator  – Traffic flow and monitoring analysis

Amlan Mukerjee, PhD: Co-Investigator – Civil engineering expertise in life cycle assessment

Rick Dobson: Co-Investigator – Collection and analysis of high resolution remote sensing data

David Banach: Geospatial data integration and analysis support

 

Project Team

Surveying Solutions, Inc. Project Team Members

Jeffrey Barlett, P.S.: Management of large datasets

Brian Dollman-Jersey, P.S.: Lead QA/QC analysis

Andrew Semenshuck, P.S.: Technical Lead

For Additional Information

Colin Brooks
Senior Research Scientist
734.913.6858
cnbrooks@mtu.edu

Steve Cook, P.E.
Project Manager
Michigan Department of Transportation
517.636.4094
cooks9@michigan.gov

 

Project Platforms

Bergen Quad-8

 



phantom

DJI Mavic Pro Collision Avoidance Small Imaging Quadcopter

 



Blimp

Aerostat/Blimp



 

mariner splash 2

Waterproof UAV



Sensors


nikon

Nikon D810

 

FLIRTau2

FLIR Thermal Cameras

 

Velodyne LiDAR Puck

Velodyne LiDAR Puck