基于热图的驾驶员认知分散估计方法（CS HI）---蔡秋纯

为了增加视觉和手动分心中的道路安全性，现代智能车辆还需要检测认知分心的驾驶（即，驾驶员的思维漫游）。在这项研究中，探讨了认知过程对驾驶员凝视行为的影响。提出了一种基于图像的驾驶员眼睛凝视分散的新颖表示法，以估计认知分散。在开放的高速公路上收集数据，并使用量身定制的协议来产生认知干扰。所创造形状的视觉差异表明，与分心驾驶相比，驾驶员在空挡驾驶时探索的区域更大。因此，训练了基于支持向量机（SVM）的分类器，即使是很小的数据集，对于两类问题也能达到85.2％的准确性。因此，所提出的方法具有使用注视信息识别认知干扰的判别能力。最后，这项工作详细介绍了这种基于图像的表示方法如何可用于其他分散驾驶检测的情况。

原文标题：Heatmap-Based Method for Estimating Drivers' Cognitive Distraction

原文：In order to increase road safety, among the visual and manual distractions, modern intelligent vehicles need also to detect cognitive distracted driving (i.e., the drivers mind wandering). In this study, the influence of cognitive processes on the drivers gaze behavior is explored. A novel image-based representation of the driver's eye-gaze dispersion is proposed to estimate cognitive distraction. Data are collected on open highway roads, with a tailored protocol to create cognitive distraction. The visual difference of created shapes shows that a driver explores a wider area in neutral driving compared to distracted driving. Thus, support vector machine (SVM)-based classifiers are trained, and 85.2% of accuracy is achieved for a two-class problem, even with a small dataset. Thus, the proposed method has the discriminative power to recognize cognitive distraction using gaze information. Finally, this work details how this image-based representation could be useful for other cases of distracted driving detection.

原文作者：Antonyo Musabini, Mounsif Chetitah

原文地址：https://arxiv.org/abs/2005.14136