school of computing, informatics, and decision systems engineering

esearch brief
Monitoring Traffic Using
Airborne Sensors
CIDSE researchers lead a
transdisciplinary multi-university team
to develop novel traffic monitoring
approaches
A team from Arizona State University and the
University of Arizona has architectured an approach
to automatically, in real-time, collect geo-reference
images from remote cameras for managing traffic.
This is done by integrating the imagery with
information on the height and GPS location of the
camera. Using this camera data, in combination with a
geographic representation (latitude-longitude) of the
area to be monitored, leads to an explicit way to georeference
the observed road and vehicle locations.
Absolute values of vehicle positions, speeds,
accelerations, decelerations and lane changes can be
determined. Initial experiments show promise in georeferencing
the airborne imagery.
Using this technology, the ASU-UA team has
developed prototype software to extract individual
vehicle trajectories from aerial video. Using this
software, one is able to identify individual vehicles
and their movement across consecutive images. By
knowing the pixel coordinates and the approximate
scale of the image, vehicle trajectories (in distance
and time) can easily be determined. The ASU-
UA team has demonstrated this technique using
aerial videos in Tucson and Phoenix. Data sets of
vehicle trajectories can also be used for calibration
and validation of microscopic traffic simulation
models. Such simulation models can then be used
for investigating possible roadway improvements
or to better explain existing and likely future traffic
conditions.
In addition, this approach is viable for collecting
aggregate traffic measures (delay, density, flow,
speed, etc.) which are extremely useful for traffic
mangers to figure out how the freeways and surface
streets are performing, especially when other ground
sensors are absent or disabled.
The CIDSE researchers are led by Professors Pitu
Mirchandani and Ronald Askin. Civil Engineering
Professor Mark Hickman leads the UA researchers.
The U.S. Department of Transportation has been
supporting the research. Also, the German Aerospace
Agency (DLR) in Berlin, Germany, collaborates with
the team. Led by Dr. Reinhart Kühne and Martin
Ruhé, DLR researchers have developed an integrated
platform that can be flown on fixed-wing planes and
helicopters to acquire and transmit images at five
frames per second and subsequently, also in real
time, determine traffic parameters such as speeds
and densities, and individual vehicle trajectories.
However, their system is expensive, especially
because it requires a high-resolution professional
camera and a high-precision inertial measurement
unit (IMU) that very accurately localizes the camera.
Instead, the ASU-UA approach uses a consumer
camera, albeit a high-end one, to capture images,
but accurately localizes the captured images on a
geo-referenced map using fast image processing
algorithms. Success of this research could lead to
having cameras on UAV’s that could be used for not
only monitoring daily traffic congestion and incidents,
but also assist in managing traffic during evacuations.
Mirchandani states, “This could revolutionize how
well and how fast we respond to traffic congestion
and incidents. I can imagine a future where a fleet
of equipped UAVs will be available for dispatching to
any location at any time, to assist first responders to
get to incidents fast and assist traffic managers to
proactively manage traffic.”
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Professor Pitu Mirchandani (left)