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Evaluating and implementing unmanned aerial systems (UAS) into bridge inspection and management methods


There has been increasing interest and use of unmanned aerial systems (UAS, unmanned aerial vehicles / UAVs, or “drones”), especially in the past 10 years. According to an AASHTO survey from March 2016, thirty-three state transportation agencies were working towards utilizing UAS for day-to-day operations (https://news.transportation.org/Pages/NewsReleaseDetail.aspx?NewsReleaseID=1466); a 2018 follow-up survey found that 35 of 44 state DOTs are using UAS and 20 have started using them in their daily operations (https://news.transportation.org/Pages/NewsReleaseDetail.aspx?NewsReleaseID=1504). This trend has been driven by the increasing capabilities of UAS including new software and computer capabilities to process UAS-collected data, and a continued interest in increasing safety for infrastructure inspectors, reducing inspections cost, and the introduction of new Federal Aviation Administration (FAA) UAS rules which make their deployment significantly more practical.

UAS can be applied to numerous applications including bridge inspections, road corridor assessment, confined space inspection, traffic monitoring, and slope stability evaluations, among others. One application of considerable interest to transportation agencies and their private sector partners is bridge inspections. Through the use of UAS, the surface and subsurface of bridge decks can be assessed without requiring the closing lanes of traffic or having inspectors exposed to traffic. The March 2016 AASHTO survey article noted that the cost of a UAS bridge deck inspection could be as low as $250, significantly less expensive than the estimated $4,600 for a representative traditional inspection. Collecting data via UAS can change the way that many elements are evaluated for most types of bridges. For bridges over rivers or other water bodies, UAS can collect data underneath or along the fascia without the need to close lanes of traffic and use of a Snooper truck or similar system currently used for inspection of hard-to-access bridge elements.

Currently, high resolution imagery and thermal imagery collected via UAS have proved to be the most useful for bridge inspections. High resolution imaging enables the inspector to objectively and reliably quantify cracking, staining, and other surface concerns. By adding three-dimensional (3D) information derived from photogrammetry and light detection and ranging (LiDAR), inspectors can locate and quantify areas with spalling and scaling and even perform volumetric analysis of the section loss and track changes over successive inspections. Thermal imaging enables the detection of subsurface delaminations. When mosaicked and georeferenced these areas can be mapped on the bridge for repairs and tracking of change over time (Brooks et al. 2017, Escobar-Wolf et al. 2017, Gillins et al. 2017, Omar and Nehdi 2017).

Additionally, the FAA has been developing and updating national regulations for the use of UAS in the national airspace, improving opportunities for practical, safe operations that follow national rules. Section 333 of the FAA Modernization and Reform Act of 2012 required UAS operators to file an airworthiness certificate to be able to operate platforms within designated areas and regulations. As of the last update (September 2016), over 7,300 Section 333 applications were submitted, with over 5,550 being approved and over 1,750 being denied. Furthermore, in August 2016, the FAA released the Part 107 regulations, requiring UAS operators to pass an aeronautical test to obtain a remote pilot certificate. The certificate allows operators to fly the platform in a large area of national airspace without prior notification, but still requires prior authorization or restricts operations in some airspace (for example, within five miles of an airport). However, operation can still take place in restricted areas with the filing and acceptance of a Part 107 waiver petition.

Despite the technological and regulatory advancements, use of UAS for collecting data for bridge management has been more limited; there has been limited research (and implementation) in how UAS-enabled data collection can be utilized for bridge management. There is a need for research on how UAS can be implemented for fast and repeatable collection of location-specific, element-level data to meet federal requirements and to support bridge owner maintenance and identification of preservation needs. Further research is needed to understand the following questions:

  • What specific bridge features, components, and elements can be assessed using UAS?

  • How easy is it to use UAS, who can use them, and how can they best be deployed – by agencies, 3rd party providers, etc.?

  • What data can/cannot be readily collected with UAS that is needed for bridge management?

  • How UAS collected data compare to data collected by current methods in terms of cost, repeatability, ease of collection?

  • Can UAS identify bridge defects at the level of detail and accuracy required to identify appropriate maintenance, repair, and rehabilitation actions as compared to conventional inspection?

  • What types of bridges are UAS most useful for – concrete vs. steel construction, small vs. complex / “big” bridges, etc.?


This research will be focused on field testing the application of UAS based bridge inspections as it relates to supporting bridge management data collection and practices. Field inspections and integration of resulting data into bridge management workflows will be used to achieve the following objectives:

  1. Determine which bridge element types are most suited to UAS assessment.

Which bridge elements have been accessed and evaluated using UAS in previous research? What bridge elements are UAS able to detect and assess? Can the bridge elements be evaluated based on qualitative and quantitative information detected by the UAS, such as identifying the defect types, their severity, and extent/quantity?

A literature review overviewing previous research that has used UAS to inspect bridges and bridge elements that are likely to be inspected through the use of UAS and remote sensing.

Objective 2. Assess UAS operation training requirements for state DOT personnel and the usefulness of hiring a third party service.

How long would it take to properly train state DOT personnel in how to use a UAS to conduct standard inspections; hours, days, weeks? What is the best way to train state DOT personnel; hands-on, manuals, a combination of both? Based on the amount of time and associated costs in training state DOT personnel, would it be more beneficial to hire a third party service that is experienced and trained in the use of UAS for inspection purposes?

Training manuals and best practices documentation in how to use UAS for inspection purposes, including cost-comparisons between training state DOT personnel and the use of a third party service.

Objective 3. Compare and contrast the types of data collected via UAS to traditional methods.

: Based on previous research and new field testing, how can optical, thermal infrared, and LiDAR data be used to identify element defects, severities, and extent/quantities? What other types of remote sensing techniques can be used to identify defects, severities, and extent/quantities? How do remote sensing methods compare to traditional manual methods, especially in terms of efficiency, cost, and repeatability? What are the benefits of using remote sensing methods as compared to manual methods and vice versa?

Based on the field tests and results, a table summarizing what types of data and what types of defects and severities can be detected using each type of remote sensing technology will be created. A report comparison between remote sensing and manual methods for specific defect types will included in the table.

Objective 4. Determine what types of required bridge management data cannot be collected via UAS and compare to traditional methods.

In contrast to Objective 3, what types of bridge management data cannot be identified and/or quantified using remote sensing technology? Are these defects located in any specific regions on the bridge? Are these defects with low severity (in the fair condition state for example)? Can traditional manual methods detect these defects better than remote sensing methods?

A report overviewing what bridge management data cannot be detected by remote sensors and how traditional manual methods are better suited for the task.

Objective 5. Compare UAS collected data to data collected by an inspector with respect to data type, quality, cost, time required, traffic impact, or other.

How do data collected using a UAS compare to traditional manual methods relating to data type/resolution, required time to collect, cost to collect, and traffic impacts?

A report comparing and contrasting UAS data to data collected by an inspector.

Results from the study will be discussed and distributed through the reports produced throughout the project as well as regular updates and presentations to AASHTO and the Transportation Research Board Annual Meeting, along with other potential venues such as state transportation research meetings recommended by AASHTO. Furthermore, training workshops will be held with state DOTs to aid in implementation efforts. Peer exchange efforts will be achieved by submitting at least one paper to a peer-reviewed journal and by attending and presenting at a national transportation conference, such as the Transportation Research Board’s annual meeting.


The anticipated products from this research include a series of related reports outlining the advantages of implementing UAS into standard bridge inspections as well as a comparison between UAS and traditional methods as they relate to bridge management. These products are designed to help lead to UAS implementation across state DOTs as part of bridge asset management where they make the most sense, including enhancing the capabilities of inspection methods for fast, repeatable collection of inspection information useful for bridge asset management. The capabilities of UAS-enabled sensing and data collection have been advancing rapidly, creating the opportunity for transportation agencies to better take advantage of them rather than having to wait longer for implementation. If the problem statement is not funded, this is likely to lead to slower implementation of UAS for collecting critical bridge condition data, delaying the ability of transportation agencies to take advantage of this new technology.

Related Research:

Previous research projects similar to this proposed effort have demonstrated the capabilities of using UAS for infrastructure assessment to transportation agencies, including collect data via UAS useful for bridge management. The Michigan Department of Transportation (MDOT) funded research in which the use of UAVs for transportation purposes were evaluated for use in highway bridge, confined space, and traffic monitoring purposes (Brooks et al. 2015). The research helped determine that UAV technologies provided many advantages to MDOT in the cost-effective assessment, management, and maintenance of its resources, with a focus on bridge inspection, while also providing benefits to their employees and the traveling public. The Minnesota Department of Transportation has been evaluating UAS for bridge inspections. Phase II of their UAS project has looked into how the senseFly Albris (a commercially packaged UAS with integrated video, still, and thermal cameras) can be used for bridge inspections (Wells et al. 2017). A 2014 Caltrans report lists eight states that have started to formally evaluate the potential applications of UAS (these include: Dobson et al., 2014; Brooks et al., 2015; Estes, 2014; Irizarry, 2014; Siskowski and Frierson, 2013; Barfuss et al., 2012; Judson, 2012; McCormack, 2008).

Similarly, UAS applications have been demonstrated to the United States Department of Transportation (USDOT) under the Commercial Remote Sensing and Spatial Information Program (http://www.rita.dot.gov/rdt/remote_sensing.html) in the application of assessing unpaved roads for defect features and overall condition rating (Dobson et al. 2014) and for post-storm event bridge and road sensing (O’Neil-Dunne and Singh 2016). The unpaved road research determined that UAS could significantly reduce the time required to assess these largely rural roads, while also increasing inspector safety and decreasing the overall costs associated with road assessments. The recent Pooled Fund Study on “The Use of Element Level Data & Bridge Management Software in the Network Analysis of Big Bridges” noted in its final report that using advanced non-destructive evaluation (NDE) methods in conjunction with UAS could “significantly reduce inspection times and access costs while improving safety of inspections” (Croop et al. 2017). At the 2018 Transportation Research Board (TRB) Annual Meeting, there were multiple dedicated sessions focused on UAS-enabled sensing, including reviews of the Michigan, Minnesota, Texas, and North Carolina DOT efforts integrated UAV-enabled sensing into their operations, with a focus on bridge inspection at MN, TX, and MI. A search of the TRB TRID database for the key words “unmanned aerial systems bridge” reveals 45 records, including publications relevant to UAS and bridge management such as Hackl et al. 2018, Salomon and Wells 2018, Brooks et al. 2017, Eschmann and Wundsam 2017, and Gillins et al. 2016, among others.

Literature cited:

Barfuss, S.L., Jensen, A., Clemens, S., 2012. Evaluating and Development of Unmanned Aircraft (UAV) for UDOT Needs. Utah Department of Transportation Research Division Report No. UT-12.08. 49 pgs.

Brooks, C., Dobson, R.J., Banach, D.M., Dean, D. Oommen, T., Escobar-Wolf, R., Havens, T.C., Ahlborn, T.M., Hart, B, 2015. Evaluating the Use of Unmanned Aerial Vehicles for Transportation Purposes. Michigan Department of Transportation Final Report No. RC1616. 201 pgs

Brooks, C., Dobson, R., Banach, D. and Cook, S.J., 2017. Transportation Infrastructure Assessment through the Use of Unmanned Aerial Vehicles. Transportation Research Board 96th Annual Meeting Compendium of Papers, No. 17-05629. 13 pgs.

Croop, B.C., Thompson, P., Ahlborn, T, Brooks, C.N., Puckett, J., Fyrster, M., Murphy, T.P., Lopez, M., Banach, D.M. The Use of Element Level Data & Bridge Management Software in the Network Analysis of Big Bridges. Michigan Department of Transportation Report No. SPR-1667, Final Report, Transportation Pooled Fund Study No. TPF-5(308). 410 pgs.

Dobson, R., Colling, T., Brooks, C., Roussi, C., Watkins, M. and Dean, D., 2014. Collecting Decision Support System Data Through Remote Sensing of Unpaved Roads. Transportation Research Record: Journal of the Transportation Research Board, 2433: 108-115.

Eschmann, C. and Wundsam, T., 2017. Web-Based Georeferenced 3D Inspection and Monitoring of Bridges with Unmanned Aircraft Systems. Journal of Surveying Engineering, 143(3), p.04017003.

Escobar-Wolf, R., Oommen, T., Brooks, C.N., Dobson, R.J. and Ahlborn, T.M., 2017. Unmanned Aerial Vehicle (UAV)-Based Assessment of Concrete Bridge Deck Delamination Using Thermal and Visible Camera Sensors: A Preliminary Analysis. Research in Nondestructive Evaluation, pp.1-16.

Estes, C., 2014. Unmanned Aircraft Use in North Carolina. Report to the Joint Legislative Oversight Committee on Information Technology Joint Legislative Transportation Oversight Committee Fiscal Research Division. 28 pgs.

Gillins, M.N., Gillins, D.T. and Parrish, C., 2016. Cost-effective bridge safety inspections using unmanned aircraft systems (UAS). In Geotechnical and Structural Engineering Congress 2016 (pp. 1931-1940).

Hackl, J., Adey, B.T., Woźniak, M. and Schümperlin, O., 2017. Use of Unmanned Aerial Vehicle Photogrammetry to Obtain Topographical Information to Improve Bridge Risk Assessment. Journal of Infrastructure Systems, 24(1), p.04017041.

Irizarry, J., Johnson, E.N., 2014. Feasibility Study to Determine the Economic and Operational Benefits of Utilizing Unmanned Aerial Vehicles (UAVs). Georgia Institute of Technology Report No. FHWA-GA-1H-12-38. 156 pgs

Judson, F., 2012. The Ohio Department of Transportation and Unmanned Aircraft Systems. LiDAR Magazine, Vol. 2, No. 5. 4 pgs.

McCormack, E.D., 2008. The Use of Small Unmanned Aircraft by the Washington State Department of Transportation. Washington State Department of Transportation Report No. WA-RD 703.1. 27 pgs.

Omar, T. and Nehdi, M.L., 2017. Remote sensing of concrete bridge decks using unmanned aerial vehicle infrared thermography. Automation in Construction, 83, pp.360-371.

O’Neil-Dunne, J. and Singh, C., 2016. Unmanned Aircraft Systems for Transportation Decision Support (No. OASRTRS-14-H-UVM Final Report). United States Dept. of Transportation, Office of the Assistant Secretary for Research and Technology.

Salomon, A.L. and Wells, J., 2018. Exploiting Imagery Data Collected with Unmanned Aircraft Systems (UAS) for Bridge Inspections. Transportation Research Board 97th Annual Meeting Compendium of Papers, No. 18-03134. 18 pgs.

Siskowski, D. and Frierson, T., 2013. Use of Unmanned Aerial Vehicles for AHTD Applications. Arkansas State Highway and Transportation Department Contract TRC-1104. 116 pgs.

Wells, J.L., Lovelace, B. and Kalar, T., 2017. Use of unmanned aircraft systems for bridge inspections. Transportation Research Record: Journal of the Transportation Research Board, (2612), pp.60-66.


This research is especially useful for a target audience focused on state transportation agency bridge managers and those providing UAS services to them. The results of this research can be used by transportation agencies as guidance on how to implement UAS-enabled sensing where this provides timely, accurate, and cost-efficient data for bridge asset management. Bridge managers and state DOT directors are likely to be key decision-makers in the adoption of this technology, with the managers, inspection teams, and third-party service providers being the practical early adopters.

The AASHTO T-18 Committee on Bridge Management, Evaluation, and Rehabilitation is likely to be a key committee for adoption of the results, in partnership with other parts of the Subcommittee on Bridges and Structures (SCOBS). T-19 (Software and Technology) and T9 (Bridge Preservation) are also likely to be important to successful adoption of UAS-enabled methods.

Based on their interest in UAS technology for bridge inspection and management, early adopters may include the Michigan Department of Transportation, the Minnesota Department of Transportation, the Texas Department of Transportation, and the Vermont Agency of Transportation, among others. Transportation agencies from Ohio, North Carolina, New Mexico, Alaska, and California have also been early adopters of UAS technology, and have been sharing their results with the transportation research community, and could also be early adopters.

Institutional and political barriers could include lack of funding for new technology, unwillingness to change from existing methods, and national UAS rules that limit longer distance flights and operations over traffic. New methods and technology have often been challenging to implement, but with advancing capabilities and the opportunity to demonstrate practical use of UAS, this barrier should be able to be overcome. National UAS rules from the FAA have been becoming more flexible, and new efforts to enable operations beyond standard rules, such beyond visual line of sight and operation over people are being tested through the FAA Pathfinder program and Part 107 waiver process.


State DOTs, local governments, practitioners, private sector, manufactureres

Sponsoring Committee:AKT50, Bridge and Structures Management
Research Period:12 - 24 months
Research Priority:High
RNS Developer:Colin Brooks, Michigan Tech Research Institute
Source Info:AHD35 committee members
Date Posted:11/20/2018
Date Modified:05/01/2019
Index Terms:Drones, Unmanned aircraft systems, Bridge management systems, Inspection, Structural health monitoring,
Cosponsoring Committees: 
Data and Information Technology
Maintenance and Preservation
Bridges and other structures

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