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Geospatial Technologies in Transportation
We conduct leading-edge research in advanced
geospatial
methodologies, much of this in collaboration with the University of
California, Santa
Barbara. Some projects are funded by the US Department of
Transportation, NASA, and the California Department of Transportation.
The technical scope of the work includes GPS tracking, map error remediation, remote sensing,
data modeling, traffic microsimulation and travel demand modeling.
Examples:
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Our Metropolitan Transportation Information System (MeTrIS) gathers densely sampled tracking data (DTD) from large numbers of
vehicles using GPS and other sensors. The DTD are analyzed and modeled
to monitor and to optimize various aspects of infrastructure and
operations in real time, and to guide policies in areas such as
congestion pricing and air quality. A current project applies MeTrIS to
drayage trucking around the ports of Los Angeles and Long Beach.
- Mapping the transportation
network.
A host of applications—LBS, ITS, EMS, retail site selection—demand
precise detail on the
transportation system: centerline geometry,
number of lanes, turn prohibitions at intersections,
and real time congestion data. There are questions about fitness for
use in location referencing, geocoding and route finding. There's a
need
for interoperability
among data bases of varying quality. We assess application needs. We
use GPS and sensing
technologies to update data; we develop algorithms for error
detection and conflation, and
communications
protocols to ensure error-free
transactions in location exchange.
- Transit planning.
Large organizations
provide
parking
to thousands of employees, at great expense. We argue that they are
potentially the most cost-effective market for transit operators,
because of the spatial concentration of travel demand. We design
optimal transit routes to serve communities of employees.
Congested
parking lots call
for better transit
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- Pavement condition. Engineers target
roads for
repair
based on visual inspection, or using van-based sensors to measure
pavement health parameters. Analyzing
sub-metre hyperspectral imagery, we're able to replicate (at least in
part) the findings of experts and ARAN-type sensors.
- Unmanned Aerial Vehicles (UAVs), from
hand-held
bumble
bees to 30-metre wing-span behemoths, are poised to revolutionize data
gathering
for transportation. We are exploring UAV sensing applications in urban
management and security.
- Planning corridors and alignments.
Determining where
to
run a new highway is a complex process, requiring detailed physical
surveys and a variety of human considerations. We explore technologies
such as Lidar and Ifsar for preliminary physical surveys, and develop
decision
support systems to facilitate the public consultation process for
rights of way and alignments.
- Data Modeling. We were part of the
technical
team
that
created the ESRI® UNETRANS template for transportation
(2001), and the Standard Labelled Road Network (SLRN) in
Ontario, Canada (1991).
- Security. Which facilities are most
critical in the
event of a disaster, and how to prioritize infrastructure for
maintenance and protection? How long does it take to evacuate a
neighbourhood? We use optimization algorithms and microsimulation to
address these issues.
We have experience with public and private sector
applications in Canada, the United States and Australia. We're actively
involved in a number of professional organizations and standards
development efforts.
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