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Dominant Driving Operations in Curve Sections Differentiating Skilled and Unskilled Drivers

机译:弯道区域的主要驾驶操作,区分熟练和不熟练的驾驶员

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Our objective is to develop a new driving assist system that can help low-skilled drivers improve their driving skill. In this paper, we describe a statistical method we have developed to extract distinctions between high- and low-skilled drivers. There are three key contributions. The first is the introduction of wavelet transform to analyze the frequency character of driver operations. The second is a feature extraction technology based on AdaBoost, which selects a small number of critical operation features between high- and low-skilled drivers. The third is a simple definition for high- and low-skilled drivers. We performed a series of experiments using a driving simulator on a specially designed course including several curves and then used the proposed method to extract driving operation features showing the difference between the two groups.
机译:我们的目标是开发一种新的驾驶辅助系统,以帮助低技能的驾驶员提高驾驶技能。在本文中,我们描述了一种统计方法,我们已经开发出这种方法来提取高技能和低技能驾驶员之间的区别。有三个主要贡献。首先是引入小波变换来分析驾驶员操作的频率特性。第二种是基于AdaBoost的特征提取技术,该技术在高技能和低技能的驾驶员之间选择少量的关键操作功能。第三个是对高技能和低技能驾驶员的简单定义。我们使用驾驶模拟器在经过特殊设计的课程中进行了一系列实验,该课程包括多条曲线,然后使用提出的方法提取了显示两组之间差异的驾驶操作特征。

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