Automated weather forecasting and treatment recommendations to support winter maintenance operations

The Federal Highway Administration (FHWA) has been sponsoring research into surface transportation weather for more than a decade. A primary focus of this effort is the development of an end-to-end winter Maintenance Decision Support System (MDSS) that utilizes advanced weather forecasting technology, road condition predictions, and automated treatment rules of practice. The system is designed to give maintenance operators strategic guidance on the type of storm conditions they are likely to see and guidance on a recommended treatment plan (plowing and/or chemicals). As an important component of the MDSS several national laboratories have worked cooperatively to develop 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 first version of the MDSS-RCTM system was demonstrated for the Iowa Department of Transportation (DOT) in early 2003 with follow-on studies in 2004 (Iowa) and Colorado (2005). Several private vendors have, or are in the process of, incorporating many of the ideas and principles of the MDSS into operational products. Previous MDSS related papers have primarily focused on the overall system and details of the weather forecasting portion of the MDSS.

This paper focuses on the RCTM including its' overall design, detailed features, limitations and demonstration experiences and results. The RCTM is composed of five main components: snow depth, pavement temperature, storm characterization, chemical concentration and rules of practice. Each algorithm and its' relations to other components are discussed in detail. In addition, both the potential for enhancements and expected limitations of the system are also pointed out. The most recent demonstration in Colorado was very useful in refining the RCTM. Demonstrations results are presented to illustrate the overall concepts of the MDSS and RCTM and to point out current limitations of the system.