# An Image Processing-Based Method to Analyze Driver Visual Behavior Using Eye-Tracker Data
## 2 Literature Review  
Several studies demonstrate that driving context could influence drivers' glance behavior [20; 21]. Studies have been conducted to evaluate both the effect of the duration of the occlusion and the different road conditions on the driver's attention [22]. [PERSON] (2002) [23] highlighted that driving on curves is riskier than driving on straight roads, and one would anticipate some shift in fixation distributions because of curvature. Driving on curves has garnered much attention, partly because it is more complex than driving on straight segments and partly because collisions are more probable. Drivers spend more time gazing at the edge lines when driving on curves than when driving straight ahead to obtain essential guiding signals. According to [PERSON] et al. (1989) [24], the time spent on the inner road edge climbs from around 10% for a straight stretch to roughly 30% for left curves and 40% for right curves of unknown radius. Drivers have a higher preview distance for wider curve radii, typically staring toward the vanishing point and scattering their fixations over a larger region [25; 26]. Drivers on sharper road curves looked at the forward road more frequently and longer [27]. Another study [28] investigated where drivers glance when approaching bends on a twisty road. Prior models of visual processes in curve driving have concentrated on path-control behavior. The occlusion point of a curve was defined in the study as the nearest point where the vision of the road was covered by some barrier (e.g., due to wild vegetation). The study revealed that drivers approach open bends on rural roads and look towards the occlusion point. Safe driving depends on appropriate visual behavior. Drivers who engage in non-visual cognitive tasks tend to focus more on the road ahead (on-path glances), neglecting off-path hazards, worsening scanning patterns, and increasing the risk of missing critical information about potential dangers [29]. Vision is crucial for lane keeping and path planning in low-traffic driving scenarios, with the gaze typically fixed on a target point determined by future car position. In complex environments like urban areas, vision is needed to monitor other drivers and traffic signs. Due to human vision's limited accuracy outside the foveal area, drivers must shift their gaze between the projected route and surrounding objects [28]. A shift in the fixation pattern is a more qualitative distinction between straight and curved parts. According to the research by [PERSON] et al. (1996) [30], a significant percentage of changes left and right are often seen at a fair distance in front of the car when driving in bends. Though similar patterns are also present in curve fixation patterns, the prevailing pattern for straight portions is thought to entail more of a straight-ahead close-far variety. [PERSON] (1993) [31], for instance, claims that the typical fixation pattern creates a series of fixes, each of which entails gazing incrementally farther down the road before making a fixation closer to the vehicle to resume the sequence. There is a tendency to glance towards the inside of curves, mainly right-hand curves. However, it is essential to note that sight distance is typically shorter along the curves' interior than the exterior. Detection of targets depends on frequent gaze direction, with curves on the right side receiving more attention, especially from experienced drivers at higher speeds. According to the study by [PERSON] et al. (1977) [32], a curve has more intense visual search activity than a straight line. When drivers are not looking at the road, crash risk is increased. In the paper by [PERSON] (2002) [23], the expected number of fatalities from an in-vehicle task can be predicted from a combination of the number of glances at the device per use, the mean glance duration, and the frequency of device use per week.