Abstract
The aim of this study is to examine drivers’ visual and driving behavior while merging onto or exiting an urban expressway with low and high traffic densities. The analysis was conducted according to three periods (approaching, merging or exiting, and accelerating or decelerating). A total of 10 subjects (8 males and 2 females) with ages ranging from 25 to 52 years old (M = 30.0 years old) participated in the study. The research was conducted in a natural driving situation, and the drivers’ eye movements were monitored and recorded using an eye tracking system. The results show that the influence of traffic density on the glance duration and scan duration is more significant when merging than when exiting. The results also demonstrate that the number of glances and the mean glance duration are mainly related to the driving task (e.g., the merging period). Therefore, drivers’ visual search strategies mainly depend on the current driving task. With regard to driving behavior, the variation tendencies of the duration and the velocity of each period are similar. These results support building an automated driving assistant system that can automatically identify gaps and accelerate or decelerate the car accordingly or provide suggestions to the driver to do so.
Highlights
Visual information is extremely vital to keep safe driving; Most studies [1,2,3,4] agree that visual information plays a significant role in driving
According to Underwood and Crundall [22], glance duration is defined as the time that the eye dwells continuously within one driver interest regions (DIRs), and the scan duration is the time that it takes to switch from one DIR to another DIR
GlanceTPerc is defined as the percentage of glance time during the task, which reflects the percentage of time that the subjects focus on a DIR
Summary
Visual information is extremely vital to keep safe driving; Most studies [1,2,3,4] agree that visual information plays a significant role in driving. A driver’s ability to perceive important information at optimal times is critical to maintain safe driving performance, and underlying visual strategies is primarily reflected by the drivers’ eye movements. Many studies [5,6] examining intersections showed that measuring and analyzing drivers’ visual behaviors could provide a better understanding of the underlying cognitive mechanisms. The research results of Ball [7] showed that compared to incorrect decisions and evaluations based on properly seen information, information deficiency was the main reason for driving errors that can lead to accidents. Romoser [8] discussed the differences in scanning behavior between older and younger drivers at an intersection; the results confirmed that some difficulties older adults had in scanning intersections were due to a specific attention deficit that
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