The Surface Transportation Weather Research Center (STWRC) was formed in January 2004. The Center is housed in the John D. Odegard School of Aerospace Sciences located on the campus of the University of North Dakota (UND).

STWRC is a university organization conducting leading edge investigations on advanced road weather data acquisition, analysis, and prediction issues associated with transportation maintenance, operations, and advanced traveler information systems.

The University of North Dakota Surface Transportation Weather Research Center will remain a national leader in road weather research and application development and will continue to engage in innovative research promoting efficiency, safety and improved mobility in support of advanced highway maintenance applications, operations, and next generation travel information systems.

STWRC's Background


Weather is a significant component in threats to surface transportation outcomes of safety, mobility, productivity, environmental quality and national security. There are approximately 6,800 weather related fatal crashes each year with an additional 450,000 injury crashes in adverse weather. Annually, over $2 billion are spent each year in providing winter road maintenance across the United States. Even a modest goal of reducing the impacts due to adverse weather by 5% will provide a tremendous benefit economically and improved safety.

Recent national studies and reports have concluded that improved availability of weather-related pavement condition information is critical to the user of the nation's surface transportation system. A national needs assessment report released in December 2002 by the Office of the Federal Coordinator for Meteorology identified over one-hundred near- and far-term weather research needs for surface transportation (OFCM, 2002). In their near-term recommendations are the development of improved analysis and prediction of pavement conditions and "integration into operational roadway transportation information systems." In addition, the 511 Coalition, an organization lead by the American Association of State Highway and Transportation Officials (AASHTO), in conjunction with many other organizations including the American Public Transportation Association (APTA) and the Intelligent Transportation Society of America (ITS America), with support from the USDOT, has released a Deployment Assistance Report (DAR) on Weather and Environmental Content in 511 Systems (AASHTO, et. al., 2003) that calls for improved weather and road condition information content. In particular, the DAR calls for the use of analyzed and predicted pavement condition information as content in future 511 systems. The Federal Highway Administration (FHWA) identified a significant need within the maintenance community for site-specific, road network-wide analyses and predictions of pavement conditions. The result of this study is the Maintenance Decision Support System (MDSS) Functional Prototype (FP) (Mahoney, 2003). A recent review of the progress of the MDSS FP has identified the lack of quality pavement condition analysis and forecast information as a critical need in transportation operations and maintenance (Burkheimer, 2003).

With a goal to provide specific guidance on short-term needs relating to advanced traveler information and Maintenance Decision Support Systems, the North Dakota and South Dakota Departments of Transportation (DOTs) identified four specific pavement condition elements that lack sufficient sophistication in analysis and prediction to provide support in either a 511 or operations and maintenance activity. In a June 10, 2003 meeting, officials of these two DOTs cited the pavement condition elements, in order of importance, of pavement frost and ice, pavement precipitation accumulation, presence of blowing and drifting snow in the roadway environment, and the reduction in visibility as the recommended items to be pursued under this project by the University of North Dakota (UND). These officials concluded that solving problems associated with these elements would provide enhanced integration of road weather management systems into traveler information, operations, and maintenance. The proposed Integration Project presented herein is a result of the recommendations of these stakeholders who will comprise the Center's Steering Committee on research and funding priorities.


STWRC's Problem Statement


Over the past two decades state departments of transportation have invested greatly in the development of roadway sensing systems and weather forecasting support for highway maintenance. Unfortunately, the state-of-the-art in surface transportation weather has advanced little in the past two decades as highway meteorology has failed to establish itself as a priority research area within the atmospheric sciences. To develop a national priority for surface transportation weather, it is critical that capable atmospheric science research institutions assume a leadership role in establishing the pathway to achieving the necessary research results. The University of North Dakota proposes through the formation of the Surface Transportation Weather Research Center (STWRC), to expand its national leadership efforts in surface transportation weather research to address critical elements that presently limit the ability to more accurately provide site-specific weather and road condition forecasts. The effort will be closely tied to existing and future regional and national ITS programs requiring weather-related support. This research effort will result from strong collaboration with state Departments of Transportation. Furthermore, the efforts at UND will be coordinated with a broader national surface transportation weather effort of the Road Weather Management Program in the FHWA.

The proposed work of the STWRC will integrate advanced pavement condition analysis and prediction system elements, which will result in greater spatial definition of pavement conditions, with ongoing and developing ITS programs in North Dakota and South Dakota. The challenge involved will be to identify new methods of problem solving associated with winter maintenance and travel safety and to develop, test and implement these methods for improved operational capabilities. Specifically, the proposed Integration Project will integrate with the current 511 traveler information systems, new road condition reporting systems becoming available during the coming year, and with the Maintenance Decision Support System presently undergoing research and development in both states.

Through the development and use of Advanced Pavement Condition Analysis and Prediction System (APCAPS) capabilities the current project will reduce the requirement for expensive road weather information system deployment throughout arterial and freeway systems. The new system will also result in improved travel planning, safety, and mobility. Further, the use of APCAPS data within operations and maintenance activities will provide improvements in new FHWA initiatives such as Maintenance Decision Support Systems (MDSS) and will improve the cost effectiveness and efficiency of winter maintenance activities.


STWRC's Research Objectives


The specific work of the Center is the application of fine-scale analysis and prediction techniques associated with pavement frost, pavement precipitation accumulation, blowing/drifting snow, and roadway visibility as part of an improved roadway weather management system, traveler information system and operations and maintenance activities. Many of the required techniques necessary to complete this task have been researched and developed through other non-surface transportation efforts. The use of modern meteorological data assimilation coupled with data quality control and correction techniques can synthesize the existing RWIS data with other surface-based meteorological observations to provide an enhanced representation of weather conditions. The proposed work will perform this data assimilation activity to provide a more robust and complete roadway weather management system. The proposed work will also incorporate into this data assimilation effort remotely sensed meteorological data that will provide greater insight into the presence of precipitation, its rate of accumulation and its redistribution due to the wind.

Further, using mesoscale modeling in combination with statistical and heuristic prediction methods the prediction of future pavement conditions resulting from spatial variations in weather conditions will be accomplished. Development of a roadway specific modeling system that incorporates the asymmetric dimensions of the roadway system will be evaluated as a potential method for reducing further the 10-kilometer resolution to be used in the initial project pavement condition work. The purpose of this roadway specific model is to overcome the problems with present forecasting methods in the roadway system that are based upon the conformance of coarser spatial model or forecast system information onto the roadway environment. Having a prediction system designed to conform to the geometry of the roadway permits more explicit prediction systems to evolve. The use of adaptive grids and finite element methods are a logical approach to this roadway modeling environment. From this modeling environment more detailed simulations/predictions could be driven by the boundary conditions derived from the existing model environments.

In addition, a reliable multi-dimensional snowdrift prediction model will be developed that provides support for road coverage (pillow drifts, finger drifts, etc.) and support for driver visibility prediction. Present models by the U.S. Army Corps of Engineers in use today (SNTHERM) are non-distributed models (only computed for a vertical column above a point). Using the roadway modeling system suggested above, this snowdrift model should be capable of being driven by improved mesoscale and misoscale prediction models. The modeling of spatial distribution of blowing and drifting snow throughout a road corridor from this model would also provide valuable information for predicting driver visibility (considering both the driver height levels of automobiles and trucks). Especially important will be the need to understand the roadside land-surface characteristics and the cross-section geometry of the roadway. This information will be valuable in a 0-6 hour prediction for the purpose of providing travel information and maintenance support.

Finally, an improved road condition model will be constructed that takes into consideration not only the heat balance condition, but also mass balance that includes the impacts of road surface contaminants. An existing operational mass balance model will be utilized as the basis in the final pavement condition prediction efforts. Again, as before, much of the detail lies in knowing what actually is found on the road surface. Another important element in this mass balance road condition model is the impact of traffic on the distribution of snow and ice on the road surface. Pavement level modeling of traffic impacts on the observed road surface will be an important element in this completed model, but are beyond the present scope of work to be performed.

This pavement conditions system, known as the Advanced Pavement Condition Analysis and Prediction System (APCAPS), will provide solutions to the spatial variability of pavement problems associated with too few RWIS observations and the inability of RWIS to predict future conditions. This APCAPS information will be integrated with other ITS systems requiring improved pavement condition data and information to promote improved safety, mobility and cost effectiveness. By leveraging the proposed efforts with other existing and proposed ITS efforts, it is expected that not only an economy of scale will be achieved, but that the time to deploy will be dramatically reduced.

The APCAPS will be part of a collection of ITS initiatives either already in place or initiatives that are soon to begin. A portion of the work will build upon previous ITS deployment activities at the University of North Dakota through activities with the North Dakota and South Dakota Departments of Transportation. The States of North Dakota and South Dakota were early developers and adopters of advanced traveler information systems in the late 1990s. Their efforts were part of a FHWA funded ITS research and deployment effort at the University of North Dakota known as the Advanced Transportation Weather Information System (ATWIS). The success of ATWIS from 1996 through 2001 resulted in the ATWIS methodologies leading to the first statewide 511 system deployment in Nebraska in late 2001. Since then both North Dakota and South Dakota have transitioned their early ATWIS systems, referred to as #SAFE, to a 511 configuration. The basis of this system is comprised of a short-range, site-specific weather forecast and the latest reported road conditions as determined by maintenance personnel and/or state highway patrol personnel. And although the weather forecasting efforts include the use of Road Weather Information System (RWIS) observations of pavement conditions, the RWIS pavement condition information is not provided to the traveler in the 511 systems due to its lack of representativeness beyond its observation location and its relevance only as an observation and not a prediction of future conditions. The proposed APCAPS will be integrated with the existing 511 systems in both states to enhance the road condition content.

Besides supporting 511, APCAPS will improve the utilization of existing and future Road Weather Management Systems (RWMS). In order to provide a reliable pavement condition observation system using existing methods requires a massive fleet of trained observers continually traveling the highway and/or freeway system or an increase in RWIS sensor locations of many orders of magnitude beyond the number presently deployed. The economic feasibility of either of these solutions is not realistic nor would such a deployment provide information on the future pavement conditions that would be encountered by travelers or require removal by maintenance personnel. The proposed activity, as will be described in more detail in a later section, will draw upon the existing RWMS, in the form of RWIS observations across North Dakota and South Dakota, to build a more extensive RWMS that can be utilized more efficiently.

The APCAPS will provide much of its information to 511 via a sophisticated road condition reporting system (RCRS) presently being designed for the South Dakota Department of Transportation by Meridian Environmental Technology, Inc. This RCRS, which will also be deployed in North Dakota during 2004, will provide the necessary support for data and information delivery following accepted ITS Standards. As a result, the information from APCAPS will be able to flow to all applications supported by the RCRS. And because APCAPS will follow ITS data standards, any RCRS following these same ITS standards will be capable of utilizing the information of APCAPS. This will permit a desired broader adoption and diffusion of the resulting ITS technologies of APCAPS beyond North Dakota and South Dakota.

The final existing ITS system in which APCAPS will be included is MDSS. As described in Section 1, the lack of quality pavement condition information having fine spatial resolution has been a problem within current MDSS development. To provide the required pavement condition information, either analyses or predictions, has been beyond the scope of work for the present MDSS initiatives. The proposed project will provide a valuable gap closer in the required information needed to make MDSS successful. The research and development to be conducted as part of the deployment process for APCAPS will prove to be beneficial for future MDSS deployments.

Research The primary focus of STWRC is research. We have targeted ten major research foci.
Weather STWRC provides up-to-date weather data, including radar imagery, temperature data, and winds speeds.
Library The STWRC Library is a growing database of documents relating to Surface Transportion research.
Staff The STWRC staff is comprised of primary researchers from the atmospheric sciences and numerous support staff.
Links Links to various institutional, regional, and national research partners.


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