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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 driver&#x2019;s mind wandering). In this study, the influence of cognitive processes on the driver&#x2019;s gaze behavior is explored. A novel image-based representation of the driver&#x2019;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. Support vector machine (SVM)-based classifiers are trained, and 85.2&#x0025; 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.

Heatmap-Based Method for Estimating Drivers’ Cognitive Distraction