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

For information concerning Phase I 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.

UAV Data

3D Mound

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 will produce practical applications of large datasets that will support MDOT’s business models and decision making processes as part of this Phase II analysis.

Examples of UAV collection

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

Task Description
Collect near real-time data from the UAV demonstrating, developing, and implementing storage capabilities of large amounts of data, usage of data, and application.
Provide data collection from UAVs to the MDOT Data Use, Analysis, and Process (DUAP) project that meets the quality, low latency delivery and data format requirements.
Provide a report that describes and recommends optimal methods to store and distribute potentially large UAV-based datasets. 
Demonstrate, develop, and implement high-accuracy simultaneous thermal/photo/video/Light Detection and Ranging (LiDAR) measurement.
Demonstrate the capabilities to complete aerial remote sensing data collections to meet MDOT mapping and construction monitoring needs.
Demonstrate, develop, and implement uses of data collection from UAV(s) and sensors for operations, maintenance, design, and asset management.
Demonstrate, develop, and implement enhanced testing of UAV-based thermal imaging for bridge deck structural integrity.
Ensure UAV sensor data collected meet the requirements of data collection systems used at MDOT.
Demonstrate, develop, and implement systems management and operations uses.
Provide a benefit/cost analysis and performance measures that define the return on investment as a result of deploying UAVs and related sensory technologies for transportation purposes.
Secure a Federal Aviation Administration (FAA) Certificate of Authorization (COA) to complete the below tasks and deliverables.

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

Steve Cook, P.E.
Project Manager
Michigan Department of Transportation


Proposed Platforms

bergen quad 8

Bergen Quad-8


Small Imaging Quadcopter


Aerostats Blimp


Collision Avoidance UAV

mariner splash 2

Waterproof UAV

Proposed Sensors

Nikon D810


FLIR Thermal Cameras

Velodyne LiDAR Puck

Velodyne LiDAR Puck