Pikalert® Vehicle Data Translator (VDT), Weather Data Translator, and Applications

Weather has a significant impact on the operations of the nation’s roadway system year round. Weather may prompt travelers to change departure times, cancel trips, choose an alternate route, or select a different mode; slick pavements, low visibility, and lane obstructions lead to driving at lower speeds or with increased following distances. These changes in behavior can reduce the throughputs at traffic signals that are timed for clear and dry conditions. Travel reliability for motorists and commercial vehicle operators is also affected by a variety of weather conditions. Weather also impacts the operational effectiveness and productivity of traffic management agencies and road maintenance agencies through increased costs and lost time.  It is, therefore, an important responsibility of traffic managers and maintenance personnel to implement operational strategies that optimize system performance by mitigating the effects of weather on the roadways. Accurate, timely, route-specific weather information, allows traffic and maintenance managers to better operate and maintain roads under adverse conditions.

The FHWA Road Weather Management Program (RWMP) is currently demonstrating how weather, road condition, and related vehicle data can be collected, transmitted, processed, and used to execute these operational strategies through the Integrated Mobile Observations (IMO) project. This presentation focuses on the RWMP efforts - Weather Data Environment (WxDE), Vehicle Data Translator (VDT) and two road weather connected vehicle applications - Enhanced Maintenance Decision Support System (EMDSS) and Motorists Advisories and Warnings (MAW).

The VDT’s role is to ingest and process mobile data already present on vehicles and incorporate those vehicle-based measurements of the road and surrounding atmosphere with other ancillary weather data. The VDT serves as a tool and a demonstration of how multi-source weather, road condition, and related vehicle data may be collected, processed, and transmitted to provide a holistic resource for accurate real-time road weather information. The WxDE is part of a holistic goal to aid in the advancement of the state-of-the-art in targeted, coordinated road weather research and development through observation, modeling, information dissemination, and supporting integrated road weather technologies.

Connected vehicle technologies hold the promise to transform road weather management. Road weather connected vehicle applications will dramatically expand the amount of data that can be used to assess, forecast, and address the impacts that weather has on roads, vehicles, and travelers; fundamentally changing the manner in which weather-sensitive transportation system management and operations are conducted. The broad availability of road weather data from an immense fleet of mobile sources will vastly improve the ability to detect and forecast road weather and pavement conditions, and will provide the capability to manage road-weather response on specific roadway links.

EMDSS and MAW are two road weather connected vehicle applications developed to improve operations and road weather information dissemination during adverse weather conditions, respectively. Fleet and passenger vehicles fitted with sensors to collect road weather information (air temperature, pavement temperature, humidity, etc.) will transmit, in real time, to the VDT. Other weather data sources like the National Weather Service (NWS) forecasts, Road Weather Information System (RWIS) stations, etc. will also transmit data to the VDT in real time. The VDT as described earlier, applies robust algorithms to process input from all these sources to provide forecasts with greater geographic and temporal resolution. These forecasts update dynamically as new data sets are continuously being sent to the VDT. Data from vehicles provide forecasts with greater geographic and temporal resolution, otherwise not available from static data sources such as Environmental Sensor Stations (ESS). Connected vehicle data will thus enhance forecasts and help identify problem segments with greater accuracy. This presentation will demonstrate how road weather information at your fingertips will assists in traveler and maintenance decision support.