Intelligent transportation
could be seen as a high-tech search for the road less traveled. It strives
for improved traffic flow to ensure safer, quicker, less expensive,
and more-energy-efficient travel.
Many intelligent
transportation systems (ITS) are being designed to better manage traffic
on well-traveled roads to reduce congestion and achieve these goals.
Inside cars, navigational systems with display panels are intended to
guide drivers around heavy traffic and help them avoid accidents. Traffic
management technologies are designed to communicate with drivers on
busy interstate highways through navigational systems and variable message
signs.
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The Federal Highway Administration
(FHWA) initiated a Dynamic Traffic Assignment (DTA) research project
to develop advanced software tools that will be used to address complex
traffic control and management issues in the information-based, dynamic
ITS environment. Under the DTA project, Rekha Pillai, Cheng Liu, Ingrid
Busch, and Charlie Davis, all of ORNL's Energy Division, along with
researchers at both the University of Texas at Austin and the Massachusetts
Institute of Technology, are developing real-time Traffic Estimation
and Prediction System (TrEPS) software tools. The goal is to help traffic
management centers (TMCs) anticipate and avert traffic congestion.
TrEPS uses traffic
surveillance data in conjunction with advanced traffic models to estimate
and predict traffic network conditions and to generate guidance for
travelers. In addition, it can interact with advanced ITS-based traffic
control systems to produce proactive traffic control actions to reduce
congestion.
TrEPS will eventually
be used by TMCs in urban areas. For example, TrEPS can provide input
to traffic managers who decide where and when to post specific messages
on variable message signs, such as AVOID CONGESTION—EXIT HERE FOR
ALTERNATE ROUTE.
"The typical operations
of traffic management centers tend to be relatively reactive in nature,"
says Bill Knéé, ORNL program manager for intelligent transportation
systems at the National Transportation Research Center (NTRC). "Using
real-time traffic data from road sensors monitoring the number of cars
and their speed, TrEPS predicts traffic conditions in the near future.
Thus, it could help TMCs become more proactive by alerting them to control
measures that lead to poor traffic flow. TrEPS also allows traffic managers
to predict how traffic flow patterns will change under what-if scenarios,
such as adding a lane or building a bridge."
Knoxville will
soon establish one of the first TMCs in Tennessee. Video cameras, road
sensors, and variable message signs will be placed along interstate
routes.
"We hope NTRC
will be a site for the Knox County Traffic Operations Center because
we can collect data and do research using TrEPS and be partners in improving
operations at the center," Knéé says. "We can use this center
to showcase advanced traffic systems technologies and traffic management
strategies."
ORNL's Energy
Division researchers became interested in doing research on ITS because
these information systems could potentially save energy by allowing
drivers to avoid congestion (unless the technologies entice people to
do more driving). But Dan Tufano and Phil Spelt, two researchers in
ORNL's Computer Science and Mathematics Division who once studied the
human factors of nuclear reactor operations, are interested in the behavioral
aspects associated with driving cars equipped with these technologies.
They want to know to what extent drivers are distracted, startled, or
annoyed by information overload as a result of ITS in cars. These technologies
include cell phones, navigational systems with map displays, voice messages,
collision avoidance warning systems, and electronic mail from the auto
PC (which can also be used for Web surfing).
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Dan
Tufano (left) practices driving while Phil Spelt watches a simulator
incorporating the car in a virtual road trip. (Photo by Tom Cerniglio.)
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At NTRC, Tufano and Spelt
will be studying people's reactions on a driving simulator, which features
a driving buck (the forward portion of a car body, with a steering wheel,
accelerator, and ITS technologies) and a screen showing the car being
driven along a computer-generated road in the presence of both other
computer-generated cars and pedestrians. They also plan to measure reactions
of drivers of DOE's research vehicle, a 1999 Dodge Intrepid that is
outfitted with ITS. The researchers may measure and compare brain-wave
patterns, heartbeat rate, and muscle tension of each volunteer when
driving a traditional car and then the research vehicle.
Meanwhile, ITS researchers
at ORNL are looking around the bend at new projects coming their way:
integrating ITS in a Smart Truck for the military and participating
in DOE's 21st Century Truck Program for developing trucks that have
improved fuel efficiency, reduced emissions, and enhanced safety.
Fortunately, smart
people are studying whether smart vehicles and smart highways are being
used in the most intelligent way.
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Related Web
sites
ORNL's
Computer Science and Mathematics Division
ORNL's
Energy Division
Federal Highway
Administration
MIT's Intelligent
Transportation Systems Program
