Driver categorization based on vehicle motion and trajectory data

The paper deals with categorization of different driving styles. The categorization is based on real-time simulator studies with several test drivers with different attitudes. The categorization of the drivers are based on the monitoring of the vehicle motion, detecting abrupt movements and speed limit violations. The goal of the study is to set up typical driving behavior categorizes, thus dangerous driver attitudes can be identified. The benefit of such driver categorization is that transportation companies can monitor their drivers using easily accessible data, which helps to avoid dangerous driving behaviors.