Many studies have demonstrated the strong relationships between physiological responses and driving stress, but they have done little to build a model that could be used to identify a driver's stress accurately in real time. The objective of this study is to develop a model that accurately classifies driving stress by monitoring physiological responses—specifically galvanic skin response (GSR). GSR data were collected from nine drivers with licenses obtained in the US in real road driving situations with two stress conditions—rest period (low stress) and highway or city driving (high stress). The validation drive was performed by one driver with licenses obtained in South Korea in real long‐term road driving situations with two stress conditions—rural area (low stress) and highway or highway under construction (high stress). Those two conditions were used to build a binary logistic regression model to classify low stress or high stress based on a driver's measured hand GSR. The overall classification accuracy of the developed model was found to be 85.3%, and the accuracy of cross validation, with a testing dataset, was found to be 83.2%. A simple logit model was developed to identify drivers' stress by incorporating their GSR data. The developed model can be embedded in a wearable device equipped with GSR sensors for drivers to detect their stress level in real time.

中文翻译：

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开发统计模型以使用皮肤电反应对驾驶压力水平进行分类

许多研究表明，生理反应与驾驶压力之间存在很强的关系，但是他们并没有做任何工作来建立可用于实时准确识别驾驶员压力的模型。这项研究的目的是开发一种模型，该模型可以通过监视生理反应（特别是皮肤电反应（GSR））来准确分类驾驶压力。GSR数据收集自在美国实际驾驶情况下有9个压力条件的两个驾驶员，这两个压力条件分别是休息期（低压力）和高速公路或城市驾驶（高压力），在美国获得了9个具有驾驶执照的驾驶员的信息。验证驾驶是由一名在韩国获得驾驶执照的驾驶员在真实的长期道路驾驶情况下进行的，该驾驶条件具有两种压力条件：农村地区（低压力）和高速公路或在建高速公路（高压力）。这两个条件用于建立二元逻辑回归模型，根据驾驶员测得的手部GSR对低压力或高压力进行分类。发现开发模型的总体分类准确度为85.3％，使用测试数据集进行交叉验证的准确度为83.2％。开发了一个简单的logit模型，通过合并驾驶员的GSR数据来识别驾驶员的压力。所开发的模型可以嵌入到配备有GSR传感器的可穿戴设备中，以供驾驶员实时检测其压力水平。被发现是83.2％。开发了一个简单的logit模型，通过合并驾驶员的GSR数据来识别驾驶员的压力。所开发的模型可以嵌入到配备有GSR传感器的可穿戴设备中，以供驾驶员实时检测其压力水平。被发现是83.2％。开发了一个简单的logit模型，通过合并驾驶员的GSR数据来识别驾驶员的压力。所开发的模型可以嵌入到配备有GSR传感器的可穿戴设备中，以供驾驶员实时检测其压力水平。