Embedded system for driver behavior analysis based on GMM

Abstract

The work presented describes a tool for driver behavior analysis. The proposal offers a contribution based on Gaussian Mixture Model (GMM) modeling technique. GMM is a powerful tool for the statistical modeling, which allows to identify specific patterns of behavior in comparison with available data. Data are obtained by the in-vehicle sensors using Controller Area Network bus (CAN bus), an Inertial Measurement Unit (IMU) and a GPS. These data allow to provide driver behavior analysis and aggressive behavior identification. This development has been tested in real-traffic situations with different drivers.