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

机译:基于统计方法的现实数据驱动风格识别算法

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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.
机译:本文介绍了一种基于车辆通信信号的驱动风格识别的新方法。这种方法的目的是将行程分类为在车辆中驱动成三类:平静,正常或侵略性。该行程是根据车辆级别进行分类的,它是(城市,农村或高速公路)驱动的道路类型和不同类型的驾驶赛事(发射,加速和制动)。选择的一组参数,选择用于考虑驱动车辆交互的每个部分,与这些事件中的每一个相关联。由于使用通信信号的使用,可以考虑车速和加速度(例如转向角或踏板位置)以外的影响因素来确定旅行中的侵略性水平。将参数从物理值转换为无量纲分数基于考虑道路和车辆类型的转换图。这些地图已由代表性的主主主主主主主主主主主主主主动性的测试阶段定义。用于定义这些地图的方法也是描述。然后证明了驱动风格得分和燃料消耗之间的相关性。该相关性说明该算法可以成功地用于区分不同的驱动样式。最后,讨论了用于驱动风格识别(DSI)算法的不同应用程序。

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