FORETELLTM is a multi-state initiative bringing Intelligent Transportation Systems (ITS) together with advanced weather systems prediction to create operational highway maintenance management and traveler information systems throughout North America. FORETELLTM participants envision a self-sustaining road and weather information system fully integrated within a wider basket of ITS services, enhancing safety and facilitating travel throughout North America. The overall goals include reducing winter-condition related road deaths by at least 15%, and creating a viable road and weather information network across the continent. Major partners in FORETELLTM include state governments, private entities, Canadian agencies and the U.S. Department of Transportation.
Weather has an enormous effect on travel and road conditions. Drifting snow, ice, fog, and gusty winds are some of the weather events that contribute to the deaths of more than 6600 U.S. and Canadian highway users every winter. Adverse conditions cut surface friction, impact highway capacities and reduce accessibility, damaging industry and rural economies alike. Over $2 billion US is spent on snow and ice control each year in North America. Despite this, estimates indicate that:
between 25 and 35 percent of inter-urban incidents occur during adverse weather conditions;
accidents increase during adverse weather by factors of between two and five; and
U.S. injury accidents alone exceed 402,000 annually due to adverse road conditions.
To help address these difficulties, one of the major technical activities of FORETELLTM is road condition forecasting. Road condition models are defined as those models which aim to nowcast and/or forecast the status of the highway pavement. In this context, "status" may be wet, dry, slushy, snowpacked, icy snow over ice, etc. Road condition models can be divided into five categories, as follows:
(a) ice prediction models
(b) local climatological models
(c) snow condition models
(d) solar gain models
(e) drifting snow models.
The literature of road condition modeling is extensive. FORETELLTM's approach is to evaluate options and proceed by (1) adopting proven methodologies, (2) combining features from successful models, (3) adding in new features where necessary to push forward the state of the art and its application to North American conditions.
FORETELLTM will use this same approach to combine LAPS, Eta or RUC-2 gridded data points for input to its road condition models across the Mid-Western states. The final paper and presentation expands on the status and scope of work for these modeling areas and the potential of the many available approaches.