Distracted driving-related accidents are a critical global issue, especially as road traffic increases in densely populated areas. To address the challenge of driver distraction, we introduce a novel
Dataset for driver behavior classification (normal, aggressive, risky) based on accelerometer (X,Y,Z axis in meters per second squared (m/s2)) and gyroscope (X,Y, Z axis in degrees per second (°/s) )
This is the code and processed data related to the publication:Dong, Y., Zhang, L., Farah, H., Zgonnikov, A., & van Arem, B. (2023). Data-driven Semi-supervised Machine Learning with Surrogate Saf
This is the code and processed data related to the publication:Dong, Y., Zhang, L., Farah, H., Zgonnikov, A., & van Arem, B. (2023). Data-driven Semi-supervised Machine Learning with Surrogate Saf
