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Weather Detection Systems use different types of sensors to detect
current weather conditions such as:
- Atmospheric water vapor
- Pavement temperatures
- Fog density
- Ice levels
- Snow levels
These sensors are often integrated with other weather-related
ITS technologies to forecast weather conditions. Road weather information
systems, for example, transmit pavement temperatures and other
information to traffic management
centers which can, in turn, make decisions on whether to apply
anti-icing chemicals or begin snowplow operations, as well as alert travelers
to
adverse driving conditions.
Many weather detection systems can generate weather forecasts
and disseminate traveler information. Other weather detection systems
can also direct the maintenance of
roads affected by
weather. Most anti-ice technologies are integrated with road weather
information systems. Combined, they create a system that can maintain
roads in adverse
weather
conditions while providing weather forecasts and informing
travelers of road conditions.
Still other weather detection systems can provide forecasts,
disseminate traveler information, and control traffic in adverse
road-weather
conditions. The
Tennessee Fog Detection and Warning System integrates fog sensors,
speed detectors, highway advisory radio, variable message signs,
and static signs. This system can predict heavy fog and
then instruct
drivers to
drive at a designated safe speed.
See also our Telecommunications
Diagrams on
Weather detection systems
can decrease the number of accidents and increase road safety by
preparing drivers and highway agencies
for
poor weather.
Road maintenance
crews can respond with greater efficiency to weather conditions
when they receive reliable information from weather sensors.
Similarly, traffic
management
centers can use information from weather sensors to control traffic
speeds and routes, thereby enforcing safe driver behavior.
Road weather information systems, which use an environmental
sensor system to collect weather and road surface data, are the
most useful
type of
technologies for measuring ice and snow levels. These systems
consist of pavement sensors
along roadways that relay information about pavement and air
temperature, precipitation
accumulation, and wind speed to remote processing units. These
units collect and relay environmental data to a central processing
unit
that is usually
located in a highway maintenance facility. Central processing
units communicate, collect,
archive, and distribute the data. The raw data are used directly
or in coordination with a service provider to prepare nowcasts
(which describe
current weather
conditions) or forecasts.
Most ice sensors measure liquid water content or use forward
scattering spectrometer probes. Liquid water content is measured
by a microprocessor
that runs an
algorithm that in turn inputs icing rate, velocity, and temperature.
With that information
it can estimate liquid water content.
This type of measurement
can be accurate to within 30%. Forward scattering spectrometer
probes
measure the diameter
of water droplets by the forward scattering of laser light
through water
drops.
Nephelometers measure the light scattered in a forward direction
by fog particles and are the most widely used and cost-effective
fog sensors.
They provide
accurate fog density measurement in a selectable output format
(visibility in distance
units or voltage proportional to fog density). These sensors
have low maintenance requirements and are designed with roadside
highway
use
in
mind; they are
small and lightweight and their light emitters and detectors
are contained within their
housing, eliminating the need for external lenses and windows.
A nephelometer sensor unit consists of an optical system, electronics,
and software for communication to a host computer. The data obtained
by the detector
are digitized
and transferred to the host computer. Once the host computer
requests fog density data from each sensor, it determines the
level of warning
based
on a pre-established
conversion equation.
Storm sensor systems use forward scatter detection technology
to measure visibility and determine the type of storm (i.e. hurricane,
snow, ice
and the like). Other
storm detection instruments measure wind speed and direction,
precipitation
amount, air temperature, relative humidity, roadway surface conditions,
and the type
and rate of precipitation.
Weather detection systems can also transmit information about
road-weather conditions to traffic management centers, which
can, in turn, disseminate
that information
to drivers via highway advisory radio, variable messages signs,
or cell and satellite phone services, and the Internet.
- Weather detection systems that are integrated with
other ITS weather technologies have had the most success in increasing
safety and
efficiency on roads in adverse weather.
- Travelers who receive real-time weather
information from weather sensors feel better prepared to respond
to adverse road conditions.
- Snow and ice sensors accurately monitor
and detect ice and snow levels.
- Nephelometers successfully detect
and monitor fog, and the software used to facilitate communication
between the sensors and host
computer is effective. Because of its highly accurate measurements, this type
of fog sensor
is frequently
deployed at airports.
- Storm detection sensors provide accurate
data about storm types and potential storm duration.
- Safety: Weather detection systems allow for improved
emergency road response as well as increased driver awareness.
- Efficiency:
Highway agencies can make more informed decisions about how to
respond to adverse road-weather conditions; travelers
can adjust their travel time, delay
trips, or change their mode of transportation.
Costs vary widely according to the scope and complexity
of the system.
In 2004, the Transportation
Research Board and the Board on Atmospheric Sciences and Climate
published "Where the Weather Meets the Road: A Research Agenda
for Improving Road Weather Services." http://www.nap.edu/openbook/0309091365/html/
The
authors suggest that poor coordination of existing
resources and knowledge has resulted in lack of implementation
of enhanced
weather
information
to a variety of users. The authors recommend establishing
a coordinated national
road weather
research program to maximize use of available road
weather information and technologies. They also suggest
standardizing
formats of
geolocated data
and improving education
and training of road weather information users.
After several years of testing,
in 2004 the Federal Highway Administration released
the Maintenance Decision Support System,
a software
tool aimed
at helping
winter maintenance managers make decisions based on
better weather forecasting information.
The software system provides specific forecasts of
road surface conditions and treatment recommendations customized
for snowplow
routes. A team
of five national
labs participated in the development and implementation
of the tool, which was tested during the winters of
2002-2003
and 2003-2004
in
Iowa. According
to the
FHWA, the road treatment guidance provided to MDSS
users addresses fundamental winter maintenance questions such
as "what," "how much" and "when." The
system then recommends a treatment plan that includes
whether to plow, whether to use chemicals and how much,
and when
to apply treatments.
A third demonstration
is scheduled to take place in Colorado in 2005. FHWA
and its testing partners expect the private sector will
simplify the
integration of MDSS
capabilities
into their winter maintenance technology product lines.
For more information see:
For the Federal Highway Administration’s MDSS
update, go to:
A road weather information system utilizes historic
and current climatological data to develop real-time
road
and weather
forecasts for roadway
users. These systems use specialized equipment and
computer programs to monitor
air and
pavement temperatures in order to predict whether
precipitation will freeze on the pavement.
Sensors collect real-time data on air and pavement
temperatures, precipitation, and the amount of deicing
chemicals on
the pavement. Combined with
information from meteorological services, they predict
pavement temperatures for
a specific area, such as a mountain pass, over a
24-hour period. These predictions
are
then transmitted to a computer at the highway agency's
winter maintenance center where
they form the basis for an effective anti-icing strategy.
Deicing chemicals must be applied about an hour before
pavement reaches
freezing temperatures
in order
to prevent ice from forming. Using portable computers
linked by modem to the central computer, maintenance
managers
can monitor conditions
and advise
motorists
and dispatch crews as necessary.
A chain-reaction collision involving 99 vehicles
in December 1990 prompted installation of a fog
detection and warning
system on
Interstate 75
in southeastern Tennessee.
The system covers 19 miles including a three-mile,
fog-prone section above the Hiwassee River and
eight-mile sections
on each side.
Traffic center
managers with the Tennessee DOT and Tennessee Highway
Patrol access a central computer
system that collects data from eight fog detectors,
and 44 vehicle speed detectors.
By continually monitoring fog and speed sensor
data, the computer system predicts and detects conditions
conducive to fog formation,
and alerts
managers when established
threshold criteria are met. Highway Patrol personnel
visually
verify onsite conditions.
Source: Tennessee Fog Detection and Warning System
http://www.benefitcost.its.dot.gov/ITS/benecost.nsf/ID/583F256CEA4239E685256AFD006764DF
Tule fog, as it is
called by residents of California’s
Central Valley, was responsible for more than 200
crashes, 130 injuries and 18
fatalities on
a stretch of I-5 between 1973 and 1994. The dense
fog typically occurs during winter months. In 1995
the California Department of Transportation (Caltrans)
installed an
automated fog warning
system that
uses nine roadside weather and visibility monitoring
stations and 36 detectors lodged in the pavement.
A computer system provides
decision support
by correlating
field sensor data with pre-determined response
scenarios. Motorists are advised of prevailing
conditions via
flashing beacons atop
static signs,
information
broadcast over advisory radio frequencies, and
messages posted on dynamic message signs. Under
the worst
conditions, when fog
is especially dense,
access to affected
areas of the highway is restricted. Caltrans reports
that the number of fog-related accidents has been
cut by nearly
70 percent
on two stretches
of I-5 and Highway
120 where the system has been installed. In 2005
the agency plans to expand the system to sections
of Highway
99.
Sources:
http://www.its.berkeley.edu/publications/UCB/99/PRR/UCB-ITS-PRR-99-28.pdf
http://www.dot.ca.gov/dist07/aboutdist7/pubs/journals/jan_mar_2003/html/janmar03.htm
A fog mitigation system monitors visibility conditions
on I-526 near the Cooper River in Charleston, South
Carolina. When weather
conditions
warrant,
motorists
are warned of adverse driving conditions.
Source: "South Carolina DOT Low Visibility Warning
System"
http://ops.fhwa.dot.gov/weather/best_practices/CaseStudies/021.pdf
ALERT uses remote sensors in the field to transmit
environmental data about flooding to a central
computer in real time.
There are various
types and
manufacturers
of ALERT hardware and software, but they are all
designed to meet a common set of communications
criteria, making
most equipment
and programs
interchangeable.
ALERT systems have become a standard in real-time
environmental data collection because of their
accuracy, reliability,
and low cost.
The benefits of using
ALERT
are a low cost/high benefits ratio, real-time data
acquisition and most of all, automated warnings.
Source: http://www.alertsystems.org/
This is an excellent source of completed
and on-going projects that focus on the testing
and deployment of advanced
technologies for
road weather monitoring and forecasting. Members
of Aurora include departments of transportation
from a number of states as well as Canadian provinces.
The
organization works closely with the Federal Highway
Administration, university
research institutions,
and various international groups. Improvement
of existing road weather information services is a
high priority
for the organization. The program Web site is
here: http://www.aurora-program.org
For
a list of its projects, go to http://www.aurora-program.org/documents/2004-2005WorkPlan_000.pdf
"Winter Road Maintenance Decision Support System Project:
Overview and Status," Paul
Pisano, Andrew Stern, William Mahoney III, William
Myers, and Dennis Burkheimer. Sixth International
Symposium on Snow Removal and and Ice Control Technology of the
Transportation Research Board Committee on Winter Maintenance,
June 7-9,
2004.
"A New Support System
for Winter Maintenance," Focus, Federal
Highway Administration, September 2004
"Where the Weather Meets the Road," Report in Brief,
The National Academies,
2004
Mahoney, William. "An Advanced Winter Road Maintenance
Decision Support System." Eleventh Annual
ITS America 2001 Meeting.
"Surface Transportation Weather Decision
Report Requirements, Preliminary Interface Requirements/Draft
version
2.0," Mitretek Systems, Inc.,
October 2000.
Last Updated:
April 6, 2005
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