Quantitative Evaluation of driver's situation awareness in virtual driving through Eye tracking analysis

TL;DR

This paper introduces a non-intrusive, eye-tracking based method to quantitatively assess drivers' situation awareness levels during virtual driving tasks, correlating well with driving performance.

Contribution

It proposes three objective gaze-based scores for perception, comprehension, and projection, providing a novel, interference-free way to evaluate driver situation awareness.

Findings

All three scores significantly correlate with driving performance.

The method offers a new, non-intrusive approach to measure situation awareness.

Scores effectively differentiate levels of driver awareness.

Abstract

In driving tasks, the driver's situation awareness of the surrounding scenario is crucial for safety driving. However, current methods of measuring situation awareness mostly rely on subjective questionnaires, which interrupt tasks and lack non-intrusive quantification. To address this issue, our study utilizes objective gaze motion data to provide an interference-free quantification method for situation awareness. Three quantitative scores are proposed to represent three different levels of awareness: perception, comprehension, and projection, and an overall score of situation awareness is also proposed based on above three scores. To validate our findings, we conducted experiments where subjects performed driving tasks in a virtual reality simulated environment. All the four proposed situation awareness scores have clearly shown a significant correlation with driving performance. The proposed not only illuminates a new path for understanding and evaluating the situation awareness but also offers a satisfying proxy for driving performance.