One of the most significant challenges with providing travelers reports on winter road conditions is the collection of information for such reports. Classifying winter road conditions for operations and traveler information has primarily been a manual process based on staff observations while performing maintenance activities. It is a resource intensive action, often required during the busiest times of winter storm response. Because reports are based on staff observations, they can also be very subjective. This leads to inconsistent and outdated reports that are of less value to travelers.
The introduction of road weather information systems (RWIS) at fixed locations along the road, mobile sensors and cameras on fleet vehicles, and advanced weather reporting have increased the availability of data for DOT staff to better understand road conditions in addition to staff observations. As the automobile industry prepares for wider deployment of Connected and Automated Vehicles (CAV), the transportation industry anticipates the opportunity to gather even more mobile data about road conditions from private vehicles.
For these reasons, ENTERPRISE commissioned this project to research the state of practice on automating or assisting staff with the classification of winter road conditions for traveler information. The objectives for the project were to assemble a Project Team to guide research and support contact with related efforts; and, research current approaches for automating or assisting winter road condition classification.