Road Surface Condition Estimation Throughout the Day and Night by Late-fusion Using the Confidence Levels of Multiple Classifiers

Abstract

In snowy and cold regions, road surface conditions change rapidly due to snowfall and temperatures. Road surface conditions need to be grasped both in daytime and nighttime to maintain a safe and comfortable road space. However, such a method has not been proposed. Therefore, this paper proposes a method to estimate road surface conditions in both day and night by using confidence levels obtained from the daytime and nighttime classifiers. The proposed method can estimate road surface conditions throughout the daytime and nighttime. In the last part of this paper, the effectiveness of the proposed method is confirmed through experiments using actual images taken by an in-vehicle camera.