Road Surface Status Classification Using Spectral Analysis of NIR Camera Images

There is a need for an automated road status classification system considering the vast number of weather-related accidents that occur every winter. Previous research has shown that it is possible to detect hazardous road conditions, including, for example, icy pavements, using single point infrared illumination and infrared detectors. In this paper, we extend this research into camera surveillance of a road section allowing for classification of area segments of weather-related road surface conditions such as wet, snow covered, or icy. Infrared images have been obtained using an infrared camera equipped with a set of optical wavelength filters. The images have primarily been used to develop multivariate data models and also for the classification of road conditions in each pixel. This system is a vast improvement on existing single spot road status classification systems. The resulting imaging system can reliably distinguish between dry, wet, icy, or snow covered sections on road surfaces.

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