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.
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.
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
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
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
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
- 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
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
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.
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.
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
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
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).
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
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,