Mustafa Demetgul, Sanja Lazarova Molnar
This study presents a real-time road surface classification system using deep learning and fuzzy logic, achieving over 95% accuracy across multiple road types.
Researchers have developed a new system to classify road surfaces in real-time using data from mobile phone cameras and accelerometers. The system uses advanced deep learning techniques to analyze images and acceleration data, distinguishing between different types of road surfaces like asphalt and gravel. By incorporating environmental conditions such as weather and time of day, the system can adaptively choose the best data source for classification using fuzzy logic. This approach could improve vehicle control systems by providing more accurate and timely information about road conditions.
