ATLAS Lab Gives Glimpse of 21st Century Intelligent Vehicles and Smart Traffic Systems

Ed Stiles
Aug. 2, 1999


Contact:
Pitu Mirchandani
520-621-2990
pitu@sie.arizona.edu


TUCSON, ARIZ. -- In the ATLAS Laboratory at the University of Arizona in
Tucson, engineers are creating traffic systems for the 21st century.

The lab is a good place to take a peek at what_s in store for drivers as we
turn the corner into the next millennium. Among other things, cars will
drive themselves and electronic traffic cops that will use blocks-long
vision to efficiently direct traffic.

Controlling traffic amounts to controlling space, explains Pitu Mirchandani,
director of ATLAS (Advanced Traffic and Logistics Algorithms and Systems)
and a professor of Systems and Industrial Engineering (SIE).

Take a freeway interchange, for instance, where an arterial street crosses
the freeway. Cars going across the freeway and those entering and exiting
all have to get through this interchange. At any given time only a few cars
can occupy the space at critical crossing points. Traffic control amounts to
deciding who gets to use that space and when _ the goal being to move the
most cars as quickly as possible.

During the next few months, Mirchandani, SIE Assistant Professor Larry Head
and other ATLAS researchers will test a system that behaves something like
an omniscient traffic cop to control such interchanges. Tests will be run at
interchanges in Tempe, Ariz.; Tucson; Seattle, Wash., and possibly Santa
Clara, Calif.

Called RHODES (Real-time Hierarchical Optimized Distributed Effective
System), it employs video cameras at the interchange, radar detectors near
the interchange and loop detectors in the pavement up to several blocks
away. These all gather data on traffic volume and speed.

This data is fed to a computer (the omniscient traffic cop) that controls
the signals at the interchange. Since the data is updated every couple of
seconds or so, the computer "knows" what_s happening to traffic right now _
in "real time," as engineers say. It then decides how to time the lights to
optimize the traffic flow.

Currently, researchers are giving the computer its initial instructions
based on traffic data they have gathered at an interchange. Doing this for
every interchange on a freeway system would take thousands of hours.
"Eventually, we want to automate this, so that we just install the equipment
and within a matter of a few hours it has learned enough about how traffic
flows through the intersection to set itself up," Mirchandani says. That
way, traffic departments could simply install the generic traffic control
system without first doing a detailed study of traffic flow.

"This system will decrease travel time anywhere from 20 to 50 percent at the
interchange," Mirchandani says. "If the intersection can handle 3,000 cars
an hour now, it might be able to handle 4,000 with this system. You have
effectively increased the capacity of the interchange without the disruption
and cost of a construction project to upgrade the intersection."

Mirchandani emphasized that he_s not building new technology. The
electronics, signals, computers and other hardware needed to do this exist
today. ATLAS is developing the algorithm and an integrated system that
control the operation. Baking a cake is a good analogy for this, he adds.
The ingredients for the cake are like the hardware. The recipe is the
algorithm. And the properly mixed and baked cake is the integrated system.

In another project, Mirchandani, SIE Assistant Professor Frank Ciarallo and
other ATLAS researchers are developing ways to control freeway access during
times of high traffic congestion. Some cities already have traffic signals
(referred to as ramp meters by traffic engineers) that control the rate at
which vehicles enter the freeway from on-ramps. But MILOS (Multi-Objective
Integrated Large-scale Optimized ramp-metering control System) will do this
in real time.

A pipe with a bunch of smaller pipes entering from the sides is a good
analogy for a freeway system, Mirchandani says. To get the fluid to flow as
smoothly as possible, it_s necessary to open certain pipes and to cut the
flow in others. In the case of freeways, the cars are the fluid and ramp
meters are the valves.

"What we do is monitor large segments of a freeway and gather traffic data
on the mainline as well as at all the on- and off-ramps," he says. "Then
traffic moving onto the freeway is regulated by the ramp meters located on
the on-ramps." MILOS gathers data at about 20-second intervals and updates
the timing of the ramp meters about once a minute.

ATLAS researchers will test MILOS in about six months along a 10-mile-long
section of a freeway in Phoenix.

The ATLAS center also has been working on an intelligent vehicle. Recently
Mirchandani and SIE Associate Professor Feiyue Wang built a car that drives
itself. It was tested on an unopened section of a freeway in Phoenix and
successfully followed another car while completely under control of an
on-board computer.

The car uses radar and a video camera to sense other cars, maintain its
position in the lane and to control speed and braking. "We visualize a
future where the driver of an intelligent vehicle would have a CD of a map
charting his route, say I-10 from Tucson to Phoenix," Mirchandani says.
"This would be a very detailed GPS map. Your car will follow that map and
get updated based on roadside reflectors." Such reflectors would be located
about every few hundred meters along the freeway. As the car_s radar
detected each of these, the car would automatically recalibrate itself with
the map using the GPS data it was receiving from satellites.

Mirchandani believes the trucking industry will be the first to use
intelligent vehicles. The driver in the lead truck would do the driving and
the following intelligent trucks would drive themselves. "If the driver in
the lead truck gets tired, another truck can take over at the front of the
line and the first driver can just fall in line and sleep while his truck
does the driving," Mirchandani says.

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Related links:
http://www.sie.arizona.edu/ATLAS

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