From Raw Gaze to Meaningful Features: Assessment of Visual Behavior in Driving Simulator

TL;DR

This paper introduces a new analytical approach combining eye movement features to assess visual behavior in driving simulators under different visibility conditions, revealing significant differences in gaze stability and blinking patterns.

Contribution

It presents a novel method integrating BCEA, saccade, and blink features, including a new fixation asymmetry metric inspired by Guzik's Index, for analyzing eye movements in driving scenarios.

Findings

Significant differences in eye movement features between baseline and driving conditions.

Reduced visibility notably affects gaze stability and blinking behavior.

The new fixation asymmetry metric provides additional insights into visual attention.

Abstract

A novel quantitative analytical approach to investigate eye movement behaviour in a driving simulator during three conditions: Baseline, Ride (simulated drive under normal visibility), and Fog (simulated drive under reduced visibility) is presented. We illustrate the proposed approach in a case study: eye tracking data from 24 participants are analyzed using 31 parameters, organized into three groups: (1) saccade characteristics, (2) Bivariate Contour Ellipse Area (BCEA) related parameters, and (3) blinking features. Across all feature groups, numerous statistically significant differences emerge between Baseline and the simulated drive conditions. Between Ride and Fog, saccade features show minimal changes (one out of 13), whereas BCEA (9 of 13) and blink features (four of 5) exhibit pronounced differences, highlighting the strong impact of reduced visibility on gaze stability and blinking behaviour. In addition to conventional gaze features, such as saccade duration, a new metric, inspired by the Guzik's Index (GI), is introduced through feature engineering to quantify fixation asymmetry along the major axis of the BCEA. The GI results suggest that gaze dispersion remains consistent across visibility conditions, but it is significantly higher during Baseline than during Fog and Ride conditions (p < 0.01). Overall, the presented findings demonstrate that a combination of the BCEA-based features with saccade and blink parameters provides a comprehensive understanding of visual attention and gaze stability in a driving simulator, while GI offers additional insights into fixation asymmetry under varying visibility conditions.