Surface status classification, utilizing image sensor technology and computer models

It is often a problem to get descriptive road status information from the automatic road weather information systems. These monitoring stations are normally equipped with meteorological sensors and road temperature sensors. Even though some monitoring stations have road status sensors and cameras, it is difficult to assess the current road condition. The problem is that the road status sensors cover only a small part of the road’s width and length and camera images are time consuming and difficult to manually evaluate. In this paper, a new automatic road status camera that gives an image of the road status and that covers a whole lane is evaluated. This means that differences the road surface within and outside of wheel tracks can be examined. Hazardous situations with wet wheel tracks and ice in-between the tracks can be detected and road users can be warned until appropriate maintenance have been performed. This new infra-red road status camera was evaluated on data retrieved during winter 2013-2014, and it was found that road conditions differ considerably during the winter, and that differences in and between the wheel tracks occur. A correlation of friction data retrieved by vehicle mounted slip wheels with this new road condition imaging system was completed. The findings indicate that slip friction measurements correlate well with the classified road conditions from the infra-red imaging system.