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5%, although the highest accuracy of 97. 2% was observed when a deep learning algorithm was applied for group 1 where the greatest number of samples were recorded. Regression models exhibited the lowest performances in all conditions, but their simplicity help adoption for embedded systems that normally have an insufficient hardware performance for running machine learning algorithms. The DTG exploited for this study is also a sort of embedded system outfitted in commercial vehicles in Korea. As a whole, the three applied methods showed satisfactory consequences with minor differences in performances. According to a report from the U. S. DOT, around 80% of road accidents could be preventable if drivers have a chance to be informed of the impending dangerous situations on the road ahead . Also, roughly 20% of the road maintenance budget is allocated to winter road maintenance in the U. S. In these regards, road slipperiness detection using connected vehicles can be highly regarded in terms of its low budget requirement as well as the seamless monitoring capability.