Heading Down the Highway: The Mobile Alert Weather Application

In a typical year, there are 1.5 million weather-related vehicle crashes in the U.S., leading to 673,000 injuries and over 7,100 fatalities. Adverse weather and the associated poor roadway conditions are also responsible for 554 million vehicle-hours of delay per year in the U.S., with associated economic costs reaching into the billions of dollars. One possible solution for mitigating the adverse impacts of weather on the transportation system is to provide improved road and atmospheric hazard products to road maintenance operators and the travelling public. With funding and support from the U.S. Department of Transportation's (USDOT) Research and Innovative Technology Administration (RITA) and direction from the Federal Highway Administration's (FHWA) Road Weather Management Program, the National Center for Atmospheric Research (NCAR) is conducting research to develop a Vehicle Data Translator (VDT) that incorporates vehicle-based measurements of the road and surrounding atmosphere with other, more traditional weather data sources, and creates road and atmospheric hazard products for a variety of users.

In the fourth phase of this research, NCAR and FHWA are partnering with three State Departments of Transportation (Minnesota, Michigan, and Nevada) to pilot a mobile alert warning (MAW) application. This application blends traditional weather information (e.g., radar, surface stations) with mobile vehicle data (e.g., temperature, yaw rate, headlight status) to diagnose current weather conditions. These weather conditions, and other road-travel-relevant information, are provided to users via web and phone applications. The MAW also provides nowcasts and short-term forecasts out to 24 hours. The MAW uses VDT road hazard algorithms, including precipitation type (rain, ice, snow, hail), qualitative precipitation amount (rain - none, light, moderate, heavy; ice - none, slippery; snow - none, light, moderate, heavy), wind conditions (wind - none, light, moderate, extreme), road visibility (fog, dust, haze, blowing snow, sleet, hail), and flash flood danger.

This presentation will outline development and testing of the MAW, as well as future directions for this research.