基于车载传感信息融合的电动汽车驾驶行为辨识

The goal of this paper is to design a driving behavior identification system in electric vehicle through the information fusion. In the system,the information of acceleration is obtained by installing a six-axis accelerometer in the electric vehicle,followed by feature extraction by multi-scale multi-fractal(MMA)algorithm(it is the first time to use the method to extract features)to characterize the fluctuations in detail,which can distinguish the driver's driving behavior. The information including speed,power,and current,are also acquired through the OBD interface to assist driving behavior identification. Random forest(RF)algorithm is first used to identify the driving behavior based on acceleration information or OBD information only. In this paper,a method that used to fuse the information is proposed. Then the method is applied to evaluating the driving behavior. It is found that this method can effectively identify the driving behavior in electric vehicle.