Real-time Applications of Weather and Pavement Data Generated by Mobile Platforms

Global Science & Technology, Inc. (GST) and Weather Telematics developed the United States' first mobile platform (vehicle-based) environmental observation network. GST's Mobile Platform Environmental Data (MoPED) is an information processing system that acquires and disseminates mobile environmental and vehicle data to government and commercial interests. Today, MoPED provides millions of mobile platform weather observations daily to the National Oceanic Atmospheric Administration's (NOAA) National Weather Service (NWS) as part of the National Mesonet Program. The Federal Highway Administration (FHWA) of the United States Department of Transportation (USDOT) also makes use of the mobile-platform based observations, particularly for pavement temperature.

National coverage of meteorological and environmental data along important transportation corridors provides enormous insight to road weather and surface conditions. Because the participating commercial fleets travel major transportation routes, the fleets provide excellent urban coverage near population centers, as well as more remote areas in between the origin and destination points of travel. Mobile platforms supplement traditional fixed weather stations from airports and road weather stations with observations that have finer temporal and spatial resolutions. Vehicles taking data observations every 10 seconds at highway speed provide data at the microscale level of spatial detail, which can highlight rapid changes in pavement temperature over relatively small distances. Mobile platforms can detect areas of potential icing or fog that otherwise would be undetected by fixed stations many miles away.

The benefit to the user is increased situational awareness, which potentially factors into decisions taken regarding travel risk. The commercial fleet can outfit indicators in the driver's cabin to alert the driver when meteorological sensors detect conditions that become a risk for icing, for example. These hazards are then mapped geographically on displays for other decision makers to monitor, or for other end users to view (i.e., motorists contemplating travel on a route where a hazard was detected). In essence, a single piece of data provides feedback to the user directly, then to decision support systems where potentially much larger user communities are made aware of a hazard detected by a single vehicle.

Moreover, the NWS is able to refine forecasts, watches, and warnings based on the detailed data provided by mobile platforms in areas that otherwise would be unsampled. NWS further benefits by assimilation of mobile platform observations in predictive models, as well as decision support tools used to communicate hazards to emergency managers and state DOT managers. Examples will be shown during this presentation.