Synthetic distracted driving (SynDD1) dataset for analyzing distracted behaviors and various gaze zones of a driver.

This article presents a synthetic distracted driving (SynDD1) dataset for machine learning models to detect and analyze drivers' various distracted behavior and different gaze zones. We collected the data in a stationary vehicle using three in-vehicle cameras positioned at locations: on the dashboard, near the rearview mirror, and on the top right-side window corner. The dataset contains two activity types: distracted activities [1], [2], [3], and gaze zones [4], [5], [6] for each participant and each activity type has two sets: without appearance blocks and with appearance blocks, such as wearing a hat or sunglasses.