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Towards real-time monitoring of fear in driving sessions

机译：实时监控驾驶过程中的恐惧

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Recent statistical analysis on road transport report that human behaviour represents one of the main causes in road traffic accidents. In this context, the application of new technologies to monitor driver’s conditions becomes essential to detect anomalous driver behaviour and to identify near miss accidents. Near miss accidents are unplanned events that did not result in injury, illness, or damage - but had the potential to do so. In dangerous goods transport by road, few accidents are reported but their consequences may be very relevant. So, the automatic detection of near miss accident may constitute an important resource to improve risk analysis. Specifically, the fundamental hypothesis of our research is that in a near miss accident, the driver’s physiological conditions vary. Among them, due to either the emotion or the fear due to a miss accident, the driver’s brain shows a variation which could be detected in real time.In this paper, an electroencephalogram (EEG)-based driver control system (EEG-DCS) is presented to monitor the driver brain activities. This study investigates the driver’s behaviour and reaction when he/she is exposed to unexpected acoustic or visual external event which perturbs a car driving session in a virtual simulated scenario. The EEG Enobio cap with eight electrodes is used to perform EEG driver’s monitoring. Signals related to alpha waves in the EEG signals have been evaluated in time and frequency domain. The analysis has clearly demonstrated that the changes in driver’s brain wave activities, visualized in the EEG, are significantly correlated to external events causing an unexpected fear to the driver.
机译：最近对道路运输的统计分析表明，人类行为是造成道路交通事故的主要原因之一。在这种情况下，应用新技术来监视驾驶员的状况对于检测驾驶员的异常行为并识别出差错事故至关重要。事故未遂事故是未计划的事件，没有造成人身伤害，疾病或损坏，但有可能造成伤害。在公路危险品运输中，几乎没有事故报告，但其后果可能非常相关。因此，对未命中事故的自动检测可能构成改进风险分析的重要资源。具体来说，我们研究的基本假设是，在一次未遂事故中，驾驶员的生理状况会有所不同。其中，由于意外事故引起的情绪或恐惧，驾驶员的大脑显示出可以实时检测到的变化。本文基于脑电图（EEG）的驾驶员控制系统（EEG-DCS）被提出来监视驾驶员的大脑活动。这项研究调查了驾驶员在意外的听觉或视觉外部事件中所遭受的行为和反应，这些事件在虚拟模拟场景中扰乱了汽车驾驶过程。具有八个电极的EEG Enobio帽用于执行EEG驾驶员的监视。 EEG信号中与α波有关的信号已在时域和频域进行了评估。该分析清楚地表明，在EEG中可视化的驾驶员脑电波活动的变化与外部事件显着相关，从而使驾驶员产生意想不到的恐惧。

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