Optimizing RWIS Information In the Decision Making Process

Today’s maintenance managers in Canada and the United States must be able to handle multiple tasks during snow and ice control operations or risk falling behind the onslaught of winter weather. Although today’s managers have a variety of good information which can lead to effective snow and ice control, all of the regulations concerning chemical applications, environmental impacts and multiple, often contradictory, weather and road weather forecasts can lead to information overload for the field operations decision maker. The Federal Highway Administration (FHWA) recognized these problems and since 1999 has been developing and field testing a Maintenance Decision Support System (MDSS) for snow and ice control operations. The MDSS project integrates state-of-theart weather and road weather forecasting, data fusion, and optimization techniques with computerized snow and ice control rules of practice logic. MDSS provides a specific forecast of surface conditions and treatment recommendations customized for individual maintenance garages snow plow routes. Treatment recommendations include the following information: • Recommended treatment plans such as plow only, chemical use, and abrasives • Recommended chemical amount (pounds per lane mile) • Timing of initial and subsequent treatments • Indication of the need to pre-treat or post-treat the road After successful field evaluations during the past two winters in Iowa, there was general agreement among maintenance managers that these new technologies were able to assist them with maintaining safety and mobility on roadways and provide for more efficient use of chemicals, equipment and staff. Private sector road weather providers also agreed there is a market for these new technologies. This paper will provide an overview of the prototype MDSS system, its successes and lessons learned in snow and ice control operations in the Midwestern United States and the 2004-2005 field tests in the more complex weather regions of Colorado. Annual maintenance savings (materials, equipment and labor) will also be discussed.