83rd Annual

Wednesday, 12 February 2003: 2:45 PM
Automated Forecasting of Road Conditions and Recommended Road Treatments for Winter Storms
Robert G. Hallowell, MIT Lincoln Lab., Lexington, MA; and G. L. Blaisdell
Poster PDF (1017.5 kB)
Over the past decade there have been significant improvements in the availability, volume, and quality of the sensors and technology utilized to both capture the current state of the atmosphere and generate weather forecasts. New radar systems, automated surface observing systems, satellites and advanced numerical models have all contributed to these advances. However, the practical application of this new technology for transportation decision makers has been primarily limited to aviation. Surface transportation operators (cars, trains, buses, etc.) in general, and winter road maintenance personnel in particular, require both a detailed assessment of the road/rail surface and guidance on recommended remedial action (e.g. applying chemicals or adjusting traffic flow). Recognizing this deficiency, the FHWA (Federal Highway Administration) has been working to define the weather related needs and operational requirements of the surface transportation community since fiscal year 2000.

A primary focus of the FHWA baseline user needs and requirements has been winter road maintenance personnel. A key finding of the requirements process was that state DOTs (Departments of Transportation) were in need of a weather forecast system that provided them both an integrated view of their weather, road and crew operations and advanced guidance on what course of action might be required. As a result, the FHWA has funded a consortium of national laboratories to prototype an integrated Maintenance Decision Support System (MDSS). The MDSS uses state-of-the-art weather forecast technology and integrates it with FHWA Anti-icing guidelines to provide guidance to State DOTs in planning and managing winter storm events.

A key component of the MDSS is the Road Condition and Treatment Module (RCTM). The RCTM is designed to bridge the gap from ambient weather forecasts (temperature, precipitation, wind, etc) to road condition forecasts (pavement temperature, snow depth, mobility, etc.) and ultimately to recommendations for chemical applications and/or snow plowing to keep the roads above a minimum level of service. The RCTM consists of five main components: road snow depth, pavement temperature, road mobility, chemical concentrations and rules of practice (recommended treatments). The components range from slight modifications of existing algorithms (SNTHERM for pavement temperature) to newly developed algorithms for mobility and rules of practice. The system is designed modularly, allowing future developers or vendors to modify or replace the baseline components.

This presentation will describe the overall architecture of the RCTM, the five main components of the system, and the potential future development of RCTM and the MDSS prototype system.

*This work is sponsored by the Federal Highway Administration under Air Force Contract No. F19628-00-C-0002. Opinions, interpretations, conclusions and recommendations are those of the author and are not necessarily endorsed by the United States Government.

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