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Detection of driver distraction based on temporal relationship between eye-gaze and peripheral vehicle behavior

机译:基于视线与周围车辆行为之间的时间关系的驾驶员分心检测

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One's state of mind is subconsciously exposed as a reaction reflecting it by external stimuli. In this work, we focus on a car driver's cognitive distraction, specifically by analyzing a driver's internal state induced during a music-retrieval task using an automatic speech-recognition system. A visual event that occurs in front of the driver when a peripheral vehicle overtakes the driver's vehicle is regarded as the external stimulus. The analysis result showed that the temporal relationship between the driver's eye gaze and the peripheral vehicle behavior depends on the driver's state. Specifically, we confirmed that the timing of the gaze toward the stimulus under the distracted state is later than under the neutral state without the secondary cognitive task. This temporal feature can contribute to the detection of the cognitive distraction automatically. A detector based on a Bayesian framework using this feature achieves better accuracy than one based on the percentage road center method.
机译:一个人的心理状态在潜意识里被暴露为一种反应,这种反应通过外部刺激反映出来。在这项工作中,我们专注于汽车驾驶员的认知干扰,特别是通过使用自动语音识别系统分析在音乐检索任务期间诱发的驾驶员内部状态。当外围车辆超过驾驶员的车辆时在驾驶员的前方发生的视觉事件被视为外部刺激。分析结果表明,驾驶员的视线与周围车辆行为之间的时间关系取决于驾驶员的状态。具体而言,我们确认了在分心状态下凝视刺激的时机要晚于没有次级认知任务的中性状态。该时间特征可以有助于自动识别认知。与使用基于百分比道路中心方法的贝叶斯框架相比,使用该功能的贝叶斯框架的检测器具有更高的精度。

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