Automated Pavement Inspection and Progress Monitoring Using Uncrewed Aerial Systems: MDOT Case Study

Tuesday, June 10, 2025

4:45 PM – 6:00 PM MT

Primary Author(s)

RS

Reihaneh Samsami, Ph.D., P.E., CAPM

Assistant Professor and MS Program Coordinator
University of New Haven
Hamden, Connecticut, United States

Co-Author(s)

Colin N. Brooks, Ph.D. (he/him/his)

Senior Research Scientist
Michigan Tech Research Institute - Michigan Technological University
Ann Arbor, Michigan, United States
Richard Dobson, MS

Research Scientist, Michigan Tech Research Institute (MTRI)
Michigan Tech Research Institute (MTRI)
Ann Arbor, Michigan, United States
Chris Cook, B.S.

Assistant Research Scientist - Geospatial Scientist, Michigan Tech Research Institute (MTRI)
Michigan Tech Research Institute (MTRI)
Ann Arbor, Michigan, United States

Submitter(s)

RS

Reihaneh Samsami, Ph.D., P.E., CAPM

Assistant Professor and MS Program Coordinator
University of New Haven
Hamden, Connecticut, United States

Abstract: The highway infrastructure sector increasingly relies on innovative tools and technologies including remote sensing and computer vision to overcome challenges in inspection, such as limited experienced staff and expanding project scopes. The objective of this research is to develop a framework to utilize Uncrewed Aerial Systems (UAS) to enhance the inspection of pavements. By reducing manual inspections, which are time-consuming and can be subjective, UAS deployment facilitates efficient data collection and analysis. High-resolution optical and thermal imagery are gathered to monitor construction progress and assess the quality of pavement operation. The proposed framework enables automated progress monitoring by capturing geometric data and tracking the placement stage, providing project managers with up-to-date progress reports. In the case of Hot Mix Asphalt (HMA) pavements, thermal imaging detects potential defects like temperature segregation, which can lead to reduced pavement performance if not addressed during the paving process. The use of thermal imaging ensures that compaction is uniform, and defects are identified in real time, preventing long-term durability issues. The proposed framework has been validated through two case studies managed by the Michigan Department of Transportation (MDOT), demonstrating its ability to improve inspection efficiency and enhance safety by reducing the need for personnel in hazardous conditions.

Learning Objectives:

Attendees can expect to learn the following from this session:

Upon completion, participants will be able to describe the key technologies used in automated pavement inspection, including remote sensing and thermal imaging.
Upon completion, participants will be able to demonstrate how to analyze and interpret data collected from Uncrewed Aerial Systems (UAS) for pavement progress monitoring and defect detection.
Upon completion, participants will be able to conduct an evaluation of pavement quality using optical and thermal imagery, identifying potential issues such as temperature segregation and uneven compaction.