Driving Style Identification Algorithm with Real-World Data Based on Statistical Approach 2016-01-1422

This paper introduces a new method for driving style identification based on vehicle communication signals. The purpose of this method is to classify a trip, driven in a vehicle, into three driving style categories: calm, normal or aggressive. The trip is classified based on the vehicle class, the type of road it was driven on (urban, rural or motorway) and different types of driving events (launch, accelerating and braking). A representative set of parameters, selected to take into consideration every part of the driver-vehicle interaction, is associated to each of these events. Due to the usage of communication signals, influence factors, other than vehicle speed and acceleration (e.g. steering angle or pedals position), can be considered to determine the level of aggressiveness on the trip. The conversion of the parameters from physical values to dimensionless score is based on conversion maps that consider the road and vehicle types. These maps have been defined from a representative set of subjectively-rated test trips. The method used to define these maps is described as well. The correlation between driving style score and fuel consumption is then demonstrated. This correlation illustrates that the algorithm can be successfully used to differentiate distinct driving styles. Finally, different applications for driving style identification (DSI) algorithm are discussed.