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Toward Safer Highways: Predicting Driver Stress in Varying Conditions on Habitual Routes

机译:迈向更安全的高速公路:在习惯路线上变化的条件下预测驾驶员的压力

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摘要

Driver stress is a growing problem in the transportation industry. It causes a deterioration of cognitive skills, resulting in poor driving and an increase in the likelihood of traffic accidents. Prediction models allow us to avoid or at least minimize the negative consequences of stress. In this article, an algorithm based on deep learning is proposed to predict driver stress. This type of algorithm detects complex relationships among variables. At the same time, it avoids overfitting. The prediction of the upcoming stress level is made by taking into account driving behavior (acceleration, deceleration, speed) and the previous stress level.
机译:驾驶员压力是运输行业中日益严重的问题。它会导致认知能力下降,导致驾驶不便,并增加交通事故的可能性。预测模型使我们能够避免或至少最小化压力的负面影响。在本文中,提出了一种基于深度学习的算法来预测驾驶员压力。这种类型的算法可检测变量之间的复杂关系。同时,它避免了过拟合。通过考虑驾驶行为(加速,减速,速度)和以前的压力水平来预测即将到来的压力水平。

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