Driving skill analysis using machine learning The full curve and curve segmented cases

N. P. Chandrasiri, Kazunari Nawa, Akira Ishii, Shuguang Li, Shigeyuki Yamabe, T. Hirasawa, Yoichi Sato, Y. Suda, Takeshi Matsumura, Koji Taguchi
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引用次数: 14

Abstract

Analysis of driving skill/driver state can be used in building driver support and infotainment systems that can be adapted to individual needs of a driver. In this paper we present a machine learning approach to analyzing driving maneuver skills of a driver that covers both longitudinal and lateral controls. The concept is to learn a driver model from sensor data that are related to driving environment, driving behavior and vehicle response. Once the model is built, driving skills of an unknown run can be classified automatically. In this paper, we demonstrate the feasibility of the proposed method for driving skill analysis based on a driving simulator experiment in a curve driving scene for both the full curve and curve segmented cases.
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运用机器学习分析驾驶技能的全曲线和曲线分段情况
对驾驶技能/驾驶员状态的分析可以用于构建驾驶员支持和信息娱乐系统,这些系统可以适应驾驶员的个人需求。在本文中,我们提出了一种机器学习方法来分析驾驶员的驾驶机动技能,包括纵向和横向控制。其概念是从与驾驶环境、驾驶行为和车辆响应相关的传感器数据中学习驾驶员模型。建立模型后,可以对未知路段的驾驶技能进行自动分类。在本文中,我们通过驾驶模拟器实验,在曲线驾驶场景中对全曲线和曲线分段情况进行了驾驶技能分析,验证了该方法的可行性。
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