The Static and Dynamic Analyses of Drivers’ Gaze Movement Using VR Driving Simulator

Abstract

Drivers collect information of road and traffic conditions through a visual search while driving to avoid any potential hazards they perceive. Novice drivers with lack of driving experience may be involved in a car accident as they misjudge the information obtained by insufficient visual search with a narrower field of vision than experienced drivers do. In this regard, the current study compared and identified the gap between novice and experienced drivers in regard to the information they obtained in a visual search of gaze movement and visual attention. A combination of a static analysis, based on the dwell time, fixation duration, the number of fixations and stationary gaze entropy in visual search, and a dynamic analysis using gaze transition entropy was applied. The static analysis on gaze indicated that the group of novice drivers showed a longer dwell time on the traffic lights, pedestrians, and passing vehicles, and a longer fixation duration on the navigation system and the dashboard than the experienced ones. Also, the novice had their eyes fixed on the area of interests straight ahead more frequently while driving at an intersection. In addition, the novice group demonstrated less information at 2.60 bits out of the maximum stationary gaze entropy of 3.32 bits that a driver can exhibit, which indicated that their gaze fixations were concentrated. Meanwhile, the experienced group displayed approx. 3.09 bits, showing that their gaze was not narrowed on a certain area of interests, but was relatively evenly distributed. The dynamic analysis results showed that the novice group conducted the most gaze transitions between traffic lights, pedestrians and passing vehicles, whereas experienced drivers displayed the most transitions between the right- and left-side mirrors, passing vehicles, pedestrians, and traffic lights to find more out about the surrounding traffic conditions. In addition, the experienced group (3.04 bits) showed a higher gaze transition entropy than the novice group (2.21 bits). This indicated that a larger entropy was required to understand the visual search data because visual search strategies changed depending on the situations.