**Deployment of Maintenance Decision Support Systems (MDSS)**

**for Winter Operations**

**By**

Paul A. Pisano

Federal Highway Administration

Road Weather Management Program

400 7th Street, S.W.

HOTO-1 Room 3408

Washington, D.C. 20590 USA

Voice: 202-366-1301

Fax: 202-366-3225

Paul.Pisano@fhwa.dot.gov

David L. Huft

State of South Dakota

Department of Transportation

Becker/Hanson Building

700 East Broadway Avenue

Pierre, SD, 57501 USA

Voice: 605-773-3358

Fax: 605-773-4713

Dave.Huft@state.sd.us

Andrew D. Stern

Mitretek Systems, Inc.

Oceanic, Atmospheric and Space Systems

3150 Fairview Park Drive South

Falls Church, Virginia 22042 USA

Voice: 703-610-1754

Fax: 703-610-1563

astern@mitretek.org

Corresponding Author: Paul A. Pisano

Submission Date: 15 December 2005

Word Count (text body): 3,525 + (6x250) = 5025

**ABSTRACT**

The art and science of road maintenance during adverse winter conditions
has long been hampered by a lack of true integration of weather
information into operations. Beginning in 1999, the Federal Highway
Administration (FHWA) began to study this deficiency with its Surface
Transportation Weather Decision Support Requirements (STWDSR) effort.
The results clearly showed that road maintenance personnel desire
better, more specific weather forecast information, which could improve
the productivity and efficiency of winter maintenance practices and
ultimately lead to improved mobility and a safer driving environment.

Beginning in 2000, the FHWA convened a team of national laboratories and
created a stakeholder group of interested personnel from State
Departments of Transportation (DOTs), private sector weather service
providers and academia. With guidance from the stakeholder community,
the laboratories combined state-of-the-art weather forecasting
capabilities with computerized winter maintenance rules of practice.
This was the genesis of the winter Maintenance Decision Support System
(MDSS) prototype. This prototype underwent several development cycles
and three seasons of field demonstrations and evaluations---two in Iowa
and one in Colorado. By 2004, MDSS technologies were mature enough for
interested private sector companies to begin to incorporate MDSS
features into their product lines and begin to provide services to State
DOTs. At this point, the FHWA MDSS effort transitioned from prototype
enhancement to a focus on technology transfer to both the private sector
and the states.

Based on the national MDSS effort, as well as related activities, a
group of eight states (led by the South Dakota DOT) initiated a
pooled-fund study in 2002 to develop and implement an operational
version of MDSS for their agencies. The study has focused upon
refinement, validation, and wide-scale deployment of sustainable MDSS
technology, as demonstrated in a successful operational testing period
over the 2004-2005 winter. Based on these complementary efforts, it is
clear that the MDSS presents a valid and viable operational strategy,
but not without its development and deployment challenges. This paper
will detail strategies for the continued evolution of MDSS technologies
into the marketplace as well as advancement of the state of the practice
of winter maintenance. Details of the pooled-fund MDSS project will be
presented as one success story of deployment.

**INTRODUCTION**

Managing winter maintenance activities is a complex endeavor. Ensuring
that the plow blades are ready when the first flakes fall is only a
small part of the task. Maintenance managers also must know the
regulations about chemical applications and environmental impacts, and
be able to analyze and make sense of multiple and often contradictory
weather forecasts. Many maintenance managers also face tight budgets.
When these factors come together, they test a public agency's skill at
meeting the traveling public's high expectations for roads to be kept
free of snow and ice. Thus, today's maintenance managers require the
ability to efficiently handle multiple tasks and process high volumes of
information, or risk getting left behind in the onslaught of winter
weather (*1*).

The Federal Highway Administration (FHWA) long recognized the challenges
faced by maintenance managers (*2*). With the creation of the Road
Weather Management Program in the late 1990s, the FHWA began to work on
improving the kinds of information that were available for winter
maintenance. At that time, weather forecasts were plentiful, and a few
companies issued route-specific forecasts; however, there was no link
between the available weather information and the decisions made by
maintenance managers about winter road treatments (e.g., the best time
to treat roads, and whether salting, plowing or a combination of
approaches is most appropriate). It was this missing link that led to
the genesis of the winter Maintenance Decision Support System (MDSS)
project (*3*). The MDSS project was a collaboration between a diverse
stakeholder group consisting of State Departments of Transportation
(DOT) maintenance practitioners, five national laboratories, and the
academic and private sector communities. The MDSS prototype project was
funded and directed by the FHWA Road Weather Management Program with
significant support from the Intelligent Transportation Systems Joint
Program Office.

**MDSS OVERVIEW**

Figure 1 shows the data flow and major components of the FHWA MDSS
prototype. Ten different numerical weather prediction models (top left,
Figure 1) provide weather forecast prediction information into a data
fusion module called the Road Weather Forecast System (RWFS). The RWFS
(top right, Figure 1) also receives surface meteorological observations
(METARS) from National Weather Service (NWS) and Federal Aviation
Administration (FAA) airport sites. The system ingests both atmospheric
and pavement data from State DOT Environmental Sensor Stations (ESS)
that are deployed along many roads. Algorithms within the RWFS component
then process the information and provide one set of forecast outputs
that can be used in the Road Condition and Treatment Module (RCTM).

The RCTM (lower right, Figure 1) contains algorithms that focus on the
state of the road surface. These include models for road temperature
prediction, snow accumulation, road and bridge frost probability,
blowing snow probability, and chemical concentration and dilution. These
routines then provide input into the rules of practice algorithm for
anti-icing and deicing. The resultant output consists of route-specific
forecasts of weather, road conditions and treatment recommendations.
Most of these can be seen in the MDSS graphical user interface (GUI)
(lower left, Figure 1).

The layout of the main GUI of the FHWA MDSS prototype (Figure 2) was
approved by a committee of State DOT maintenance practitioners. It was
developed so that maintenance personnel would be able to quickly peruse
the screen and determine if there were any weather hazards forecast in
their area.

The top left portion of the GUI (in Figure 2) contains the alert status
window. This window uses easily distinguished color-coded bars to alert
users if there are forecast hazards due to weather, deteriorating road
conditions, blowing snow or road frost. The middle left window allows
the operator to select different observations or forecasts. These values
can be displayed on the main GUI window. The bottom of the GUI provides
a time scale controller to allow for animating forecast data in the main
GUI screen. There are also color coded bars that show which hours
specific routes could be affected by road frost or blowing snow. The
main display screen provides high resolution topographical backgrounds
along with displayed observed and forecast information.

One innovative module that was developed for the MDSS prototype was
called the "what-if" generator (Figure 3). This capability allows an
operator to modify the timing, chemical type or application rate on any
of the routes to see how the changes might affect the treatments or
forecast road condition. In the example shown in Figure 3, the total
number of plowing and chemical application passes was decreased (from 4
to 3). In addition the amount of applied chemical was reduced (from 200
to 100 pounds per lane mile). The resulting alternative set of inputs
(as shown with a dark blue trace on the graph) shows that snow will
begin to accumulate on the route. The green trace shows the snowfall
accumulation rate if no treatments were made.

The MDSS is a complex amalgam of computer hardware and algorithms. As
such, it is unlikely that many (if any) State DOTs have the expertise or
desire to own or operate an entire MDSS. It is more likely that states
interested in MDSS capabilities will contract with a private sector
weather service provider so that only display software would need to
reside in DOT maintenance facilities. For this reason, numerous private
sector weather service providers have been encouraged to participate and
have been engaged in the stakeholder group to develop the MDSS
prototype. The intent is to get as many companies involved as possible,
and provide to them the prototype software, thereby making deployment as
fair and seamless as possible.

The MDSS prototype was demonstrated and evaluated over three winter
seasons in Iowa and Colorado (*4*). While there are still scientific
challenges to be overcome in both weather forecasting and understanding
the complexities of winter road conditions, the MDSS project has been
quite successful in bringing the winter maintenance and weather
communities closer together and to help seed the weather service
industry with new advancements.

**FOCUS ON DEPLOYMENT**

The FHWA has invested several years in funding and guiding the
development of the MDSS prototype. However, the success of the program
was not accomplished in a vacuum. A stakeholder group gathered at least
annually during the multi-year requirements gathering and system
development process. This group was used as a sounding board at each
step and played a significant role in the GUI design and the selection
of the type of forecast elements that were to be available to the end
users. This stakeholder process also provided buy-in and involvement
from the private sector. The ultimate deployment of MDSS will depend on
the private sector recognizing that there is a market for these
capabilities and that integrating (some or all) modules into their
product lines is worth their investment.

By the end of 2005, FHWA had sponsored seven MDSS stakeholder meetings
with interest and attendance continuing to climb with each. Figure 4
shows that from 2000 through 2005, 37 U.S. States (73%) participated in
one or more MDSS stakeholder meetings. Oregon is shaded in brown because
they have shown an interest in MDSS technologies but could not attend
the meetings.

The MDSS deployment strategy, however, goes beyond just annual meetings.
FHWA has a multi-faceted program to educate and promote deployment of
MDSS technologies. The following sections highlight these strategies.

**Technology Transfer**

FHWA has established a multi-tiered technology transfer program for the
deployment of MDSS technologies. Technical guidance is geared towards
the two key stakeholder groups of State DOTs and private sector weather
service providers. For the State DOTs, the focus is on procurement of
MDSS, and for the weather service providers, the focus is on technical
implementation of the software. All MDSS prototype software has been
made available at no cost. This includes all of the source code for the
treatment algorithms, the numerical weather models and the Java-based
GUI. The RWFS data fusion module is licensed to the National Center for
Atmospheric Research (NCAR). However, they are making the object code
available for free use for a year to allow interested parties to test
and evaluate the entire package. Registration to receive the latest MDSS
prototype software can be obtained at:

[www.rap.ucar.edu/projects/rdwx_mdss/release3/](http://www.rap.ucar.edu/projects/rdwx_mdss/release3/).

During the summer of 2004, FHWA sponsored a full day technology transfer
workshop that allowed all interested parties to obtain copies of the
latest software. Engineers and scientists that developed the system gave
seminars and were available to answer questions. FHWA also funded NCAR
to provide telephone support to any party that had procurement,
installation or operating questions about the MDSS prototype software.

**Outreach and Education**

Staff from FHWA's Road Weather Management program and scientists from
NCAR have provided dozens of presentations and published numerous papers
and articles on the development, evaluation and deployment of MDSS
technologies. Some of the more well known organizations where MDSS
presentations have been made include:

-   Transportation Research Board (TRB)

-   American Meteorological Society (AMS)

-   Intelligent Transportation Society of America

-   Institute of Transportation Engineers (ITE)

-   Standing International Road Weather Commission (SIRWEC)

-   World Road Association (PIARC)

-   American Public Works Association (APWA)

-   Canadian Meteorological and Oceanographic Society (CMOS)

During the spring of 2004, FHWA co-sponsored the filming of a 30-minute
television program with The Weather Channel. The segment, called *Road
Risk*, visually depicted the dangers of driving in wet, snowy and icy
conditions. Digital Video Disks (DVDs) of the program can be obtained
from the FHWA Road Weather Management web site at
[www.fhwa.dot.gov/weather/](http://www.fhwa.dot.gov/weather/).

NCAR continues to maintain a website which serves as the main repository
for MDSS prototype presentations and documentation. The site contains
technical descriptions of the software, summaries from the stakeholder
meetings and tutorials on how to use the MDSS prototype GUI. The address
for this site is
[www.rap.ucar.edu/projects/rdwx_mdss/](http://www.rap.ucar.edu/projects/rdwx_mdss/).

Finally, FHWA has created a one-page flyer that provides background
information, shows highlights of the MDSS prototype GUI and provides a
list of potential benefits of using MDSS technologies. The MDSS flyer
can be downloaded from the FHWA Road Weather Management web site.

**Supporting Documentation**

Several State DOTs have already begun to include requirements for MDSS
functionality into their weather support contracts. To assist states in
understanding what new technologies may be on the horizon and to help
them understand how to incorporate the requirements for new technologies
into their request for proposals (RFPs), FHWA's Road Weather Management
program can provide technical assistance. NCAR has also created a
document that provides a template for creating a MDSS-centric RFP. This
document is available from

[www.rap.ucar.edu/projects/rdwx_mdss/documents/MDSS_Procurement_Template27Nov04.pdf](http://www.rap.ucar.edu/projects/rdwx_mdss/documents/MDSS_Procurement_Template27Nov04.pdf).

In an effort to capture the state-of-the-art in weather forecasting and
future trends, NCAR has also created the document "Road Weather
Forecasting and Observations: Assessment of Current Capabilities and
Future Trends." This document is available from

[www.rap.ucar.edu/projects/rdwx_mdss/documents/Weather_Observation_Prediction_Capability_Assessment_10Dec04.pdf](http://www.rap.ucar.edu/projects/rdwx_mdss/documents/Weather_Observation_Prediction_Capability_Assessment_10Dec04.pdf).

**DEPLOYMENT EXAMPLE -- THE SOUTH DAKOTA POOLED FUND PROJECT**

It took only until 2002 for several states to realize that technologies
such as the MDSS may be a good investment. As the expectations for road
mobility continued to rise by the traveling public and commercial
carriers, State DOTs continued to be constrained by both funding and
staffing. A core group of five states pooled funds to begin development
of an operational MDSS.

The pioneering group of states in the Pooled-Fund (PF) effort included
South Dakota (as the lead state), Indiana, Iowa, Minnesota, and North
Dakota. During 2005, three additional states -- Colorado, Kansas and
Wyoming - joined the pool. The states along with their contractor,
Meridian Environmental Technology, had as their goal to build and
evaluate an operational and sustainable MDSS to improve the ability to
forecast road conditions in response to changing weather and applied
maintenance treatments.

The essential elements of the PF MDSS include (*5*):

-   Reporting actual road surface conditions

-   Reporting actual maintenance treatments

-   Assessing past and present weather conditions

-   Assessing the present state of the roadway

-   Predicting storm-event weather

-   Recognizing resource constraints

-   Identifying feasible maintenance treatments

-   Predicting road surface behavior

-   Communicating recommendations to supervisors and workers

To realize these essential elements, the PF team not only had to build
upon the foundational work completed in the FHWA MDSS prototype, but
expands upon it by adding new innovations. This included equipping
snowplows with Geographic Positioning Systems (GPS) Automated Vehicle
Location (AVL) devices that are capable of reporting weather conditions
and equipment status (e.g., plow blade position). The goal was to be
able to obtain in near real-time, the location of each truck, the plow
blade position, the chemical application rate and the types of materials
used. There were also other challenges such as communicating the state
of the road surface (e.g., snow depth) into an automated system.

Like the FHWA MDSS prototype, the PF MDSS used a series of weather
models and a pavement model that provided forecast guidance on elements
such as pavement temperature, pavement chemical concentration, pavement
moisture types and depths. However, unlike the FHWA MDSS prototype, the
PF MDSS predicts road conditions and recommends maintenance treatments
on the basis of physical modeling, rather than rules of practice. The PF
MDSS added radar data, near term (tactical, under 6 hour) forecast
support, and the provision for meteorologist intervention in the weather
forecast process. Also different in the PF MDSS is the capability for
the operator to select either an 'optimal' treatment recommendation
(e.g., safety first, cost considerations second), or a 'standard'
treatment based solely on local maintenance practices. Finally, similar
to the prototype, the PF MDSS has a 'what-if' capability to allow the
user to try any number of alternative maintenance actions and see the
resulting forecast effects on the road surface (*6*).

Figure 5 shows an example of the PF MDSS main display with radar data
overlaid on a highway map. The different colors represent precipitation
phase (liquid, freezing, and frozen). The box in the center of the
screen shows an observation from a snowplow with GPS/AVL equipment
reporting location, weather and road conditions.

Figure 6 provides an example of the PF MDSS forecast and treatment
recommendation screen. Through the use of graphical visualization, the
series of tables shows probabilities of precipitation, snow
accumulations, precipitation types, forecast road conditions, treatment
recommendations and forecast road temperatures.

**NEXT STEPS FOR MDSS**

The FHWA MDSS prototype continued its limited deployment in Colorado
during the winter of 2005-2006 where there is continued evaluation of
how the system operates in complex terrain. This was sponsored by the
E-470 Public Highway Authority and the City and County of Denver,
Colorado. The PF MDSS was also undergoing field trials during the winter
of 2005-2006 in the eight pooled fund states. Once an evaluation is
completed, full deployment is expected in 2006 and 2007.

During the 2005-2006 and 2006-2007 winter seasons, the participants in
the PF MDSS project plan to expand field trials to include more
locations in the eight participating states and more extensive use of
vehicles equipped with on-board instrumentation and AVL. The project
will include validation of forecasts of weather, road conditions, and
treatment effectiveness, as well as refinement of physical models and
software. Finally, the project will address issues relating to statewide
deployment, including operational environments, business models, and
linkages to other state information systems. The ultimate goal of the
project is to provide a sustainable, fully functional, and easily
scalable MDSS to support the needs of transportation agencies.

FHWA will continue to actively promote the deployment of MDSS throughout
2006 and beyond, including further efforts pertaining to all the
technology transfer items described above, as well as possible field
evaluations. In addition, FHWA is planning on sponsoring a MDSS
stakeholder meeting in late summer/early fall 2006. Updates on both
programs as well as new deployment initiatives will be discussed. It's
clear that deployment of such a complex system takes time. State DOTs
must be confident that the services provided by the private sector work
as they should and reap benefits. Private sector providers must have the
technical wherewithal to provide the services, and know that their
investments will be profitable. While there's every reason to think that
both sets of needs can be met, it will still take time to get there.

**CONCLUSION**

In an effort to create a link between the winter road maintenance and
meteorological communities, the FHWA has directed and funded a
multi-faceted campaign to both develop a MDSS and to provide technology
transfer support and outreach so that the greater community understands
and embraces these technologies. The FHWA will be able to claim success
in this endeavor if State DOT agencies create a market for these
advanced technologies and the private sector moves to integrate these
capabilities into their product lines.

A significant step has already been taken by a group of eight State DOTs
as they have pooled their resources to develop a customized MDSS for
their agencies. FHWA continues to provide technology transfer support
and educational outreach activities to assist all parties in
understanding and nurturing this concept into reality. The benefits to
everyone in the success of this project are safer roads, more efficient
use of resources and more targeted (reduced) use of chemicals.

**REFERENCES**

1\. Pisano, P.A., A.D. Stern, and W.P. Mahoney. The U.S. Federal Highway
Administration Winter Road Maintenance Decision Support System (MDSS)
Project: Overview and Results. *American Meteorological Society
Preprint, the 21^st^ International Conference on Interactive Information
Processing Systems (IIPS)*, San Diego, CA, 2005, Paper 6.5.

2\. Mahoney, W.P., B. Bernstein, J. Wolff, S. Linden, W. Myers, R.
Hallowell, J. Cowie, A. Stern, G. Koenig, G. Phetteplace, P. Schultz, P.
Pisano, and D. Burkheimer. The Federal Highway Administration's
Maintenance Decision Support System Project: Summary Results and
Recommendations, *Transportation Research Record, Journal of the
Transportation Research Board*, National Research Council, Washington,
D.C., publication Spring 2005.

3\. Mahoney, W.P. and W. Myers. Predicting Weather and Road Conditions:
Integrated Decision Support Tool for Winter Maintenance Operations.
*Transportation Research Record*, *Journal of the Transportation
Research Board, No. 1824*, TRB, National Research Council, Washington,
D.C., 2003, pp. 98−105.

4\. *The Maintenance Decision Support System (MDSS) Project Technical
Performance Assessment Report, Colorado Field Demonstration Winter
2004-2005*, version 1.0, National Center for Atmospheric Research,
Boulder, CO, September 2005.

5\. David L. Huft, *Maintenance Decision Support System Pooled Fund
Study TPF-5(054)*, presentation made to the MDSS Stakeholder Meeting on
10/20/05 in Boulder, CO,

> www.rap.ucar.edu/projects/rdwx_mdss/plans_reviews/Sess3-MDSS_for_Stakeholders_Huft2_talk3.pps

6\. Mewes, J, R Hart, L. Osborne and B. Podoll, The Pooled Fund Study
Maintenance Decision Support System: A Functional Overview. *American
Meteorological Society Preprint, the 21^st^ International Conference on
Interactive Information Processing Systems (IIPS)*, San Diego, CA, 2005,
Paper 6.6

**LIST OF FIGURES**

FIGURE 1. MDSS functional structure (data and process flow). Ten
different weather models and sources of observations feed into the Road
Weather Forecast System (RWFS). The RWFS integrates and processes each
set of data and provides optimized forecast elements to the Road
Condition and Treatment Module (RCTM). The RCTM contains algorithms for
road temperature prediction, chemical concentration and the rules of
practice for anti and de-icing. The resulting forecast information and
treatment recommendations flow to the user displays.

FIGURE 2. MDSS prototype Graphical User Interface (GUI). The GUI
consists of several distinct sections that are optimized for the
maintenance manager. The alert screen (top left) shows color coded bars
representing forecasts of weather and road condition. There are also
indicators for blowing snow and bridge frost potential. The weather
selection box (center left) provides the ability to display many
observed and forecast fields. The animation control box (bottom) allows
the user to change forecast times and to create an animation of forecast
parameters. The main display (top right) provides high resolution
topographic backgrounds and graphics depicting observed data and
forecasts.

FIGURE 3. The MDSS 'what-if' Scenario treatment selector. This 'what-if'
selector is provided with the MDSS prototype system. It provides a way
for the operators to provide alternative treatment strategies including
using different chemicals, application rates and times. The result is
provided as a time series (top) that shows the consequences of deviating
from the recommended parameters. This capability can be used to work
around scheduling conflicts or to test and see if changing the
application strategy would still produce acceptable mobility on roads.

FIGURE 4. Total MDSS stakeholder participation 2000-2005. Thirty seven
states participated in at least one MDSS activity during the system
development years of 2000-2005.

FIGURE 5. The Pooled Fund (PF) MDSS main display. The PF version of the
MDSS GUI not only provides high resolution backgrounds and observations
but also provides data from mobile observations and color-coded weather
radar.

Figure 6. The PF MDSS forecast treatment recommendation screen. Like the
prototype MDSS display, the PF version provides advanced visualization
graphics on precipitation type and accumulation, road temperature
forecasts and treatment recommendations specifically tailored for winter
maintenance personnel.

![](media/image1.png){width="6.495833333333334in"
height="4.280555555555556in"}

Figure 1 -- MDSS functional structure (data and process flow). Ten
different weather models and sources of observations feed into the Road
Weather Forecast System (RWFS). The RWFS integrates and processes each
set of data and provides optimized forecast elements to the Road
Condition and Treatment Module (RCTM). The RCTM contains algorithms for
road temperature prediction, chemical concentration and the rules of
practice for anti and de-icing. The resulting forecast information and
treatment recommendations flow to the user displays.

![](media/image2.png){width="6.488194444444445in"
height="4.102083333333334in"}

Figure 2 -- MDSS prototype Graphical User Interface (GUI). The GUI
consists of several distinct sections that are optimized for the
maintenance manager. The alert screen (top left) shows color coded bars
representing forecasts of weather and road condition. There are also
indicators for blowing snow and bridge frost potential. The weather
selection box (center left) provides the ability to display many
observed and forecast fields. The animation control box (bottom) allows
the user to change forecast times and to create an animation of forecast
parameters. The main display (top right) provides high resolution
topographic backgrounds and graphics depicting observed data and
forecasts.

![](media/image3.png){width="6.25in" height="5.197916666666667in"}

Figure 3 -- The MDSS 'what-if' Scenario treatment selector. This
'what-if' selector is provided with the MDSS prototype system. It
provides a way for the operators to provide alternative treatment
strategies including using different chemicals, application rates and
times. The result is provided as a time series (top) that shows the
consequences of deviating from the recommended parameters. This
capability can be used to work around scheduling conflicts or to test
and see if changing the application strategy would still produce
acceptable mobility on roads.

![](media/image4.png){width="6.489583333333333in"
height="3.888888888888889in"}

Figure 4 -- Thirty seven states participated in at least one MDSS
activity during the system development years of 2000-2005.

![](media/image5.png){width="6.49375in" height="5.240277777777778in"}

Figure 5 -- The Pooled Fund (PF) MDSS main display. The PF version of
the MDSS GUI not only provides high resolution backgrounds and
observations but also provides data from mobile observations and
color-coded weather radar.

![](media/image6.png){width="6.493055555555555in"
height="5.129861111111111in"}

Figure 6 -- The PF MDSS forecast treatment recommendation screen. Like
the prototype MDSS display, the PF version provides advanced
visualization graphics on precipitation type and accumulation, road
temperature forecasts and treatment recommendations specifically
tailored for winter maintenance personnel.