# Heatmap-Based Method for Estimating Drivers' Cognitive Distraction

arXiv: https://arxiv.org/abs/2005.14136 · HTML: https://mlsanity.com/paper/2005.14136/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 May 2020.

## Built on by (most cited first, 2 of 2)

- [Survey and synthesis of state of the art in driver monitoring](https://mlsanity.com/paper/2110.00472/) (2021)
- [EyeCue: Driver Cognitive Distraction Detection via Gaze-Empowered Egocentric Video Understanding](https://mlsanity.com/paper/2605.07859/) (2026)

## Abstract (arXiv)

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 drivers mind wandering). In this study, the influence of cognitive processes on the drivers gaze behavior is explored. A novel image-based representation of the driver'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. Thus, support vector machine (SVM)-based classifiers are trained, and 85.2% 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.