FHWA Road Weather Managment Program Integrated Mobile Observations (IMO) Project

On average, there are over 5.8 M vehicle crashes each year of which 23% are weather-related. Weather-related crashes are defined as those crashes that occur in adverse weather (i.e., rain, sleet, snow, fog, severe crosswinds, or blowing snow/sand/debris) or on slick pavement (i.e., wet pavement, snowy/slushy pavement, or icy pavement). The vast majority of most weather-related crashes happen on wet pavement and during rainfall: 74% on wet pavement and 46% during rainfall. 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. Connected vehicle technologies hold the promise to transform road-weather management by providing improved road weather data in real time with greater temporal and geographic accuracy. 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. As a result the U.S. Department of Transportation's (USDOT) Federal Highway Administration (FHWA), and the Research and Innovative Technology Administration (RITA) have been jointly working to promote safety, mobility and productivity on the nation's surface transportation system by advancing road weather research. With funding and support from the USDOT and direction from FHWA Road Weather Management Program (RWMP), several connected vehicle applications have been developed. These applications use vehicle-based measurements of the road and surrounding atmosphere with other, more traditional weather data sources, and create road and atmospheric hazard products for a variety of users. 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. 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 for decision making through an innovative Integrated Mobile Observations project. FHWA is partnering with three State Departments of Transportation (Minnesota, Michigan, and Nevada) to pilot these applications. One is a mobile alerts application called the Motorists Advisories and Warnings (MAW) and the other is a maintenance support application called the Enhanced Maintenance Decision Support System (EMDSS). These applications blend 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 now casts and short-term forecasts out to 24 hours while the EMDSS application can provide forecasts up to 72 hours in advance. Both applications use 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. The three states partnering with the USDOT have placed readers and external road weather sensors on their maintenance fleet vehicles to collect vehicular and meteorological data. Data from all three states is sent to a processing house called the Vehicle Data Translator (VDT) that checks data quality and uses the data to infer current and forecasted weather conditions. This data is then used by the road weather connected vehicle applications to provide advisory warnings to motorists and maintenance recommendations to the operations crew. The differences in the size, scope, methods and outcomes of these prototypes in each state are a reminder that agencies considering deployment of this technology should evaluate their needs and capabilities on an individual basis. In addition, it is important to continue considering the needs of end users and maintenance operators for successful deployment of new technologies. This paper describes the how each state implemented the MAW and EMDSS prototype and what they learned in the process. During implementation of this prototype each state encountered several roadblocks (related to data management, interface design, coordination with OEMs, Hardware and Software designs, etc.) native to their operations and geography. Understanding these roadblocks can prove very useful to several agencies planning to deploy connected vehicle application prototypes in their regions. The paper also describes another research initiative that developed the Weather Data Environment (WxDE). This data environment acquires, validates, stores, and shares transportation-related weather data to DOT and drivers. It is part of a broader goal to advance state-of-the-art targeted, coordinated road weather research and development to better support drivers. The WxDE focuses on weather data associated with connected vehicle applications and collects data in real-time from both fixed environmental sensor stations (ESS) and mobile sources (such as DOT Fleet vehicles), and pulls together these inputs to enhance current weather and travel information. It can provide real values for observed data as well as inferred weather conditions from vehicle data (e.g., inferring precipitation based on windshield wiper activation). Sharing and integrating this weather-related transportation information enhances the Department of Transportation's ability to understand and forecast the impacts of adverse weather on roadways. It better enables the DOT to identify threats, and proactively respond to preclude and mitigate weather impacts.