January/February
2001
Safe
Plowing - Applying Intelligent Vehicle Technology
by
Robert A. Ferlis, Shahed Rowshan, and Cathy Frye
Improving
highway safety and increasing mobility are two of the bedrock goals
of the Federal Highway Administration (FHWA). These goals are constant
- 24 hours every day, seven days every week - in good weather and
bad.
In treacherous winter weather, FHWA meets some of its toughest challenges
to safety and mobility. In some states, such as Minnesota, weather
is a contributing factor in one out of every five vehicle crashes.
When weather forecasters predict snow or blizzard conditions, they
often warn people to stay at home and to keep off the roads. Usually,
they will mention the threat of slippery road conditions that can
result in a rash of car crashes. However, there is less discussion
of another serious winter hazard - the increase in cross-lane and
run-off-the-road crashes because the road markings and boundaries
are obscured by snow.
We count on our highway maintenance people to clear the snow off the
roads, but how do the snowplows stay on the road? How can the snowplow
operator find the edge of the road when it is buried under deep snow?
This can be a problem anywhere, but it is particularly dangerous in
mountainous terrain where the consequences of running off the road
are most severe.
In November 1999, former U.S. Secretary of Transportation Rodney E.
Slater announced that a $3.9 million grant was awarded to the Minnesota
Department of Transportation (MnDOT) to conduct a Specialty Vehicle
Field Operations Test. Combined with the contributions of other partners
in this three-year project, the total budget is $6.5 million. This
project will tap intelligent vehicle technology to enable snowplow
operators to "see" the roadway that is hidden to the human
eye by deep snow or white-out conditions and thereby improve safety
during plowing operations while also decreasing road closures or slowdowns
due to winter weather conditions.
Because snowplow operators routinely face the hazardous duty of clearing
slippery, snow-covered or ice-coated roads with perhaps the additional
dangers of high winds, blowing snow, or white-out conditions, intelligent
vehicle technology is being rigorously tested in Minnesota on state-owned
snowplows. In addition to the hazards from the weather, snowplow operators
must also cope with the dangers of hidden objects covered by snow
and with improper visual cues from previous plowing. MnDOT snowplows
are involved in 131 collisions annually, while in 1999, the California
Department of Transportation (Caltrans) recorded 194 accidents for
vehicles involved in snow operations. In 1998, these accidents cost
MnDOT $1.8 million in property damage and $450,000 in damage to Twin
Cities snowplows, and in 1999, the cost to Caltrans in snow removal
operations for vehicle accidents and personnel injuries was $390,679.
That's a hefty annual price tag for both states.
But how do you avoid plowing into something you cannot see? Give snowplows
360° radar to detect moving objects, make use of Global Positioning
System technology and a geo-spatial database that enables a driver
to determine where lane boundaries and the presence of fixed objects
such as guardrails and mailboxes, and then alert the driver via the
vehicle's collision warning system. Caltrans has successfully demonstrated
the use of magnetic guidance technology in which the vehicle is guided
by an in-vehicle computer that tracks magnetic markers embedded along
the center of a lane 1.2 meters apart to define the roadway.
If the snowplow operator can't see the road, what about the motorist
that may be traveling behind the snowplow with his/her visibility
decreased by the snow throwing of the plowing operation? Give snowplows
a rear-mounted, external strobe light to keep motorists at a safe
distance and to reduce rear-end collisions between motorists and snowplows.
Still, there is the battle that snowplow operators fight with stress
brought on by the intense concentration needed to maintain safe and
efficient control of a snow-removal vehicle. How do you avoid creating
more driver stress through information overload? Give drivers a voice
during the development and testing period so that their feedback can
influence improvements to the design of intelligent vehicle enhancements
and test under real conditions using real snowplows and real operators.
Winter weather can lead to another problem - potential damage to the
nation's economy. When road closures due to winter weather are unavoidable
being able to operate just two hours a day has an incredible impact
on the economy. Safe and efficient plowing is an economic requirement.
Closed or impassable roads reduce mobility and wreak havoc with deliveries
of goods to businesses and with the ability of workers to get to their
places of employment.
"In Minnesota, if all major state roads were closed for 24 hours,
estimates of the cost in lost wages, lost retail activity, and lost
economic activity exceed $100 million," said William Gardner,
Intelligent Vehicle Initiative (IVI) program manager for MnDOT's Guidestar
Intelligent Transportation Systems (ITS) program.
In California, four of the eight major highways into and out of the
state require snowplow operations to keep them open during the winter.
Closure of Interstate 80's Donner Pass would affect shipment of goods
to Nevada, Idaho, and Utah as well as affecting the 21 ski resorts
around Lake Tahoe and the entertainment business in Reno, Nev. The
financial effect of a closure of the Donner Summit for 24 hours on
gaming interests in Reno alone is estimated at approximately $10 million.
I-5. which runs north-south the length of California, is a major transportation
corridor for international commerce related to the North American
Free Trade Agreement, and a closure of I-5 would have serious international
trade consequences. So, better plowing not only means increased safety,
but it is also good for business.
High-Tech
Solutions to Age-Old Problems
Researchers involved in the Specialty Vehicle Program Partnership
are working together on two major efforts headquartered in Minnesota
and California. While the goals are the same - develop and test intelligent
vehicle-enhanced snowplows that are safer and more efficient - the
approaches differ due to regional weather conditions.
"California is more heavily populated than Minnesota and must
contend with heavy traffic as well as mountainous conditions with
deep snow cover," said Roy Bushey, program manager for the Caltrans
New Technology and Research Program.
"Unlike conditions in California, it's not the depth of the snow,
but the blowing, that creates problems here," said MnDOT's Gardner.
Drivers in both states must deal with the problem of poor visibility
caused by blowing snow. However, Minnesota has more prolonged ice
and snow problems, and California has snow to a greater depth. Minnesota
generally gets about 1.25 meters (50 inches) of snow per year, and
the state spent more than $31 million on snow removal during 1997-1998.
California receives an average of 10.7 meters (35 feet) of snow in
the mountains of central and northern California, and the state spent
more than $28 million for snow removal in 1999-2000.
Plowing
- Minnesota Style
The efforts of Minnesota, with partners 3M, the University of Minnesota,
Altra Technologies, the Minnesota Department of Public Safety, McLeod
County, Hutchinson Ambulance, and FHWA, are aimed at creating "a
driver-assistive system that will help these vehicles stay in their
lanes and avoid crashes," said Gardner.
"All of the technologies to be employed have been under development
for several years and currently are in testing on snowplows on Trunk
Highway 19 and Trunk 101," Gardner said.
The Minnesota team's efforts have yielded snowplow enhancements that
rely on the use of a differential global positioning system (DGPS)
and a geo-spatial database to locate fixed objects, such as lane boundaries
and signposts. Carrier Phase DGPS can be accurate to the two-centimeter
level. This highly accurate DGPS, combined with highly accurate geo-spatial
databases (elements of the database are mapped to accuracies of greater
than 15 centimeters), provides a high-fidelity means to provide lane-keeping
information to a driver. The geo-spatial database can be constructed
from a number of sources, including photogrammetry data and drive-overs
by vehicles equipped with highly accurate DGPS and data acquisition
equipment. The geo-spatial database is stored in a computer onboard
the snowplow.
Collision-avoidance information is sensed by a radar array on the
vehicle, and it uses the geo-spatial database to determine which radar
returns arise from fixed objects in the geo-spatial landscape that
pose no threat to the driver and which returns arise from obstacles
that do pose a threat. Only those returns that indicate a threat are
given to the driver in the form of a warning through the driver interface.
This minimizes false alarms to the driver, and increases the drivers'
acceptability.
A Magnetic Lateral Warning and Guidance System developed by 3M uses
a special magnetic tape to "outline" the lane. This magnetic
pavement marking tape can be used in place of regular lane striping.
The tape can be either grooved into the existing pavement and secured
with an adhesive or underlayed during construction, and it is detected
by a magnetic sensor on the snowplow. The sensor indicates to the
driver the vehicle's lateral position within the lane, has a lateral
detection range of +/- one meter (approximately three feet), a detection
height of 15 to 45 centimeters (6 to 8 inches) referenced from the
magnetic tape to the sensor, and an accuracy of +/- two centimeters
or +/- five centimeters depending on the lateral distance relationship
of the sensor to the magnetic tape.
A central computer interprets the data from subsystems to paint an
image of what the road would look like if weather conditions were
not preventing the driver from seeing it. This image is projected
onto a partially reflective, partially transmissive curved piece of
ground optical glass that the driver looks through. Developed by the
University of Minnesota, this Heads Up Display (HUD) flips down much
like a sun visor so that it can be used when needed and placed out
of the way when visibility is not bad enough to warrant its use. Using
the HUD, the driver can see the lane boundaries projected onto the
snow-covered roadway and can see the location of obstacles that impede
safe travel. Looking through the HUD, the driver focuses about nine
meters (30 feet) in front of the snowplow, which is normal for most
drivers.
"A key aspect is to design these systems so that they are useful
and not burdensome to drivers," said Gardner.
"You're not invincible with intelligent vehicle technology,"
warns John Scharffbillig, the project's technical services manager.
"But this is an added safety measure for situations when snowplow
drivers would have to be out clearing the roads anyway."
To ensure safety, critical subsystems have backups. Multiple radar
devices are used so that if one is not operating, another can take
its place and transmit the required data. While asking snowplow operators
to trust intelligent vehicle technology, developers are aware that
that trust must be earned. System redundancy is helping to gain that
trust; nevertheless, Scharffbillig admits, "it takes a certain
amount of faith."
One assumption is that real-time DGPS communication will not be available
100 percent of the time when it's needed. That is, the link between
the snowplow and the DGPS satellite will fail. Although the latest
DGPS receivers reacquire lock in 10 to 15 seconds, this is more than
enough time for a plow performing snow-removal operations to go off
the road or cause a collision. However, inertial measurement provides
guidance during the loss of satellite lock while also providing vehicle-orientation
information. Challenges arise as the snowplow moves in and out of
signal range, causing communication dropouts. One solution to sustained
loss of satellite lock is to determine the lane boundaries by detecting
the magnetic tape on the roadway.
System developers use familiar controls to make operators more comfortable
and to earn the operators' trust more easily and quickly.
"We use a joystick to control the hydraulics; the HUD is like
watching a TV screen; and the controls use eye-thumb coordination
like a video game," explains Scharffbillig.
A hallmark of the Minnesota intelligent vehicle development project
has been the developers' insistence that all of the intelligent vehicle
equipment must be usable without requiring the operator to make an
unnatural motion. For example, when using the HUD, drivers need not
take their eyes off the road. They perceive the enhanced road image
as painted over what they would normally see through the windshield.
All of the data is integrated into a single display that requires
no head turning and allows the driver to keep his hands on the steering
wheel at all times.
California has taken a different approach using a display firmly attached
to the cab for safety reasons. In case of an accident, there is nothing
that might come in contact with the driver's head.
The
California Solution
The Advanced Snowplow Driver Assistance System (ASP) is under development
in California and Arizona. This program combines the efforts of the
Advanced Highway Maintenance and Construction Technology (AHMCT) Research
Center at the University of California at Davis (UCD), the California
Partners for Advanced Transit and Highways (PATH) at the University
of California at Berkeley (UCB), and the Western Transportation Institute
(WTI) of Montana State University (MSU). The California DOT (Caltrans)
and the Arizona DOT (ADOT) have provided test sites and snowplow operators.
Now in the third winter of development, ASP, also know as RoadView
is using intelligent vehicle systems and advanced vehicle control and
safety systems (AVCSS) technologies. ASP has been tested through two
winters of heavy use in both California and Arizona. Two additional
snowplows are being developed for further testing this winter and next
winter as part of the RoadView project. Major ASP components include
a main computer, a human/machine interface (HMI) with a visual display
that shows the snowplow operator how the snowplow is positioned in the
lane, and two forward radar sensors that allow full coverage of three
lanes ahead of the snowplow - useful when using either a left- or right-mounted
wingplow. Azimuth angle data collected from the radar sensors also enable
the system to map detected obstacles and inform the driver about the
obstacle and the specific lane in which that obstacle is located. The
system also provides the distance (rounded to the nearest foot) to the
nearest obstacle.
|
ASP
features include a main computer, human-machine interface, forward
radar sensors, and magnetometers. |
Off the shelf magnetic markers are embedded into the roadway to create
a marker reference system. These magnetic markers can be coded to
provide various roadway information by arranging their magnetic poles
in specific patterns, which can be read via onboard magnetometers.
The California team is currently extending this discrete magnetic
marker approach to automate the steering of a 4,000-ton-per-hour rotary
plow.
Because any marker at the pavement level or higher might be scraped
away by the snowplow, embedded materials were chosen for use in this
study. At Donner Summit, the painted lane markings are usually completely
scraped off by the end of the winter season, often much more quickly.
Information collected from the magnetic markers and other sources
is relayed to a computer that interprets the data and provides an
image on the HMI visual display. When an obstacle is sensed, the Collision
Warning System (CWS) displays this information on the HMI screen.
The HMI is located where a rear-view mirror would traditionally appear
and presents information to the driver in a single, coordinated interface.
|
This
ASP Human-Machine Interface is mounted on the windshield. Some
of the worst visibility conditions on the planet can be overcome
with the aid of the ASP cab-mounted display, which receives its
data from the plow's collision-warning system. Radar sensing assists
human sight to find the road and obstacles that may be in the
way of the plow. |
Developers
gave considerable thought to the method of presenting information
gathered by intelligent vehicle systems. Early experiments verified
the research team's expectation that a "look down" sensing
system must provide "look ahead" data so the operator has
an indication not only of where the vehicle currently is but where
it will be. After all, people drive by looking out at the road, not
through the floorboard. To support this, a steering shaft encoder
was added to the system to support the prediction of the vehicle's
path. Being able to "see" the upcoming curves in the road,
the vehicle's current location, and the vehicle's predicted path,
the driver can determine the appropriate steering angle. The ability
to accurately provide this prediction is a significant advantage of
the magnetic marker-based approach.
The California platform provides the driver with a highly accurate
view of where the vehicle is and a prediction of where it will be,
whereas the Minnesota approach presents an augmented view of the road
as it appears in real time to the driver. Different approaches for
different circumstances, with both sets of enhancements making plowing
safer and more efficient.
What
Will It Cost?
The current estimate for a mass-produced California ASP unit is in
the range of $20,000 to $30,000, which does not include the vendor's
profit margin. Cost of infrastructure installation for the test sites
is approximately $11,000 per kilometer ($17,000 per mile), including
surveying, installation, and magnets. The infrastructure installation
costs have been reduced over the past few years.
"Costs have come down, which creates more potential for new equipment
to be cost-effective or even for retrofits to be cost-effective,"
said Minnesota's Scharffbillig. "The basics of these technologies
have been out there. We're just refining them to meet our needs."
|
Caltrans'
Advanced Rotary Plow uses radar sensing to avoid buried obstacles
obscured by deep-packed snow and ice. When under full automation,
this plow can be within five to fifteen centimeters (two to six
inches) from the guardrail, and its front-discharge rotary blower
is capable of clearing 3,600 metric tons (4,000 short tons) of
snow per hour. |
On
the Horizon
In both Minnesota and California, operators and managers continue
to provide valuable feedback, and the research teams are making improvements
to the system based on these suggestions. The rapid deployment of
the California ASP system into operation - the first plow deployed
within five months of the project start in 1998 - represents an early
success in the application of intelligent vehicle and AVCSS technologies
for specialty vehicles. In the long term, there are no limitations
to the application of the ASP technologies because these technologies
are applicable across all vehicle platforms, including passenger vehicles,
commercial vehicles, and transit vehicles. The same is true of the
Minnesota research, either technology may find its way into the family
car in the future.
Robert
A. Ferlis is the team leader of the Enabling Technologies Team
for the Office of Operations Research and Development in the Federal
Highway Administration. He has served as the cross-cutting coordinator
of the Intelligent Vehicle Initiative (IVI) Program since 1998. In
this position, he supports research in vehicle-highway cooperation
and is currently responsible for managing the IVI research in advanced
snowplow technology. Before joining FHWA in 1997, he worked for 10
years as a transportation research consultant with KPMG Peat Marwick
and another 10 years as a systems manager in the energy industry.
He received a bachelor's degree in engineering from the University
of Illinois and a master's degree in civil engineering from Northwestern
University.
Shahed
Rowshan was formerly a highway research engineer on the Enabling
Technologies Team for the Office of Operations Research and Development
in the Federal Highway Administration. He worked in FHWA research,
development, and technology from 1990 to 2000, and he was FHWA's IVI
specialty vehicle technical director from 1999 until his resignation
from FHWA in January 2001. As technical director, he managed the IVI
research in advanced snowplow technology. He received a doctorate
in civil engineering from the University of Maryland and is a registered
professional engineer.
Cathy
Frye is the founder of The Fresh Eye, a woman-owned sole proprietorship
established in 1994 to provide writing, editing, and publications
management services. She holds a degree in writing from Johns Hopkins
University and has more than 20 years of experience as a writer and
editor. She has worked on various FHWA projects in the past, including
the 1997 and 1998 Research and Technology Program Highlights
reports. When not writing on transportation issues, Frye can frequently
be found working in health care. Her most recent project was serving
as the editor of Perioperative Services, a comprehensive resource
book for operating room managers. Published last April, this book
is already in its second printing.
Working
to Make High-Tech User-Friendly
Developers
of driver-assisted systems for snowplows are cautiously addressing
human factors issues.
"We're trying to present drivers with additional information
without overloading them," says William Gardner, Intelligent
Vehicle Initiative program manager for the Guidestar Intelligent
Transportation Systems Program in Minnesota. The Minnesota team's
improvements are capable of projecting an outline of the roadway
- including line markings - onto a flat glass screen that the
driver can look through.
Avoiding information overload means listening to the drivers'
reactions to the equipment and working closely with them. The
project's spirit of cooperation between the snowplow operators
and developers is noteworthy, recognizing that even small changes
can make a big difference. For example, initially, the Heads Up
Display (HUD) used on Minnesota's test snowplows presented all
road markings in monochromatic yellow until the drivers requested
that white lines be shown as white and the yellow-marked lines
as yellow.
The extra information provided by color coding was more useful
to drivers than developers had assumed. Today, the system uses
color coding.
Also, originally, moving obstacles being tracked were identified
by a circle placed around them. The circle would grow larger as
the object came closer, smaller as the object receded. Unfortunately,
this presented a problem with depth perception. Developers are
now testing various icons, including a semicircle and open square,
for targeting objects.
Other system elements have also been adjusted to reflect driver
input. For example, the vibrational warning in the seat and steering
wheel that acts as a virtual rumble strip was annoyingly strong
for some drivers, while others reported that it was too weak to
get their attention. This feedback is helping the Minnesota Department
of Transportation find the most widely accepted setting. Screen
luminescence is another system element that varies widely. "This
seems to be tied to age," said John Scharffbillig, the project's
technical services manager. He noticed that older drivers requested
a brighter, more intense image and points out that resolving the
problems discovered in many of these observations required the
expertise of the University of Minnesota's Human Factors Research
Laboratory.
Continuous field testing by the California Department of Transportation's
Maintenance Program has yielded the same type of comments from
drivers and has resulted in similar system modifications. Initially,
their human/machine interface (HMI) display was mounted on top
of the dashboard near the driver's right hand. The guiding principle
for the display is to provide the necessary information to the
operator without any unnecessary informational clutter. When one
driver suggested moving the display to the rear-view mirror position,
his explanation was simple: give shorter drivers a less obstructed
view of the right-hand wingplow mirror. Interviews with other
drivers revealed that this was a popular idea, and the design
was quickly modified to incorporate it.
While augmenting human senses with intelligent vehicle technology,
developers have a heightened awareness of the possibility of introducing
what Scharffbillig calls "unintended consequences."
The solution is for developers and snowplow drivers to rigorously
test the equipment and address the human factors issues raised
by incorporating high-tech equipment into snowplows. Through their
work together, the resulting improved snowplow is well on the
road to being a human-friendly machine designed to give the driver
a significant advantage in safety and efficiency over today's
equipment. |
Other
Articles in this Issue:
Learning
to Beat Snow and Ice
Safe
Plowing - Applying Intelligent Vehicle Technology
Improving
Roadside Safety by Computer Simulation
Using
the Computer and DYNA3D to save lives
LS-DYNA:
A Computer Modeling Success Story
Preservation
of Wetlands on the Federal-Aid Highway System
Internal
FHWA Partnership Leverages Technology and Innovation
New
Applications Make NDGPS More Pervasive
Center
for Excellence in Advanced Traffic and Logistics Algorithms and Systems
(ATLAS)
National
Work Zone Awareness Week (April 9 to 12) - Enhancing Safety and Mobility
in Work Zones