# An Image Processing-Based Method to Analyze Driver Visual Behavior Using Eye-Tracker Data
## 5 Discussion  
The method proposed to analyze the eye-tracker data on gaze locations requires a series of data processing steps to overcome the lack of 3D information in the collected data. As already argued, the lack of 3D vision means a lack of information about where the gaze position and road borders are in 3D space and the distance between them. Consequently, for all the reasons stated above, it is vital to set specific guidelines to overcome this significant limitation as much as possible. Of course, the link between the 2D images and the 3D model of the circuit can overcome this limitation, but it must be carefully planned before the simulations are integrated with them. Accurately analyzing gaze position according to road borders requires consideration of the effect of perspective. Placing the road boundary coordinates in the same y-coordinate as the gaze or the projection of the gaze on the base of the building (when the gaze is on a building facade) is ideal. Please see Figure 7 for the cases mentioned above. However, this kind of placement can be time-consuming and sometimes not even possible in situations where the gaze or the projection of the gaze is not parallel to the road borders, such as when the driver is looking straight ahead to the horizon. To address this limitation, a \"ratio\" variable approach has been proposed, where the gaze is considered inside the road boundary if the ratio is between 0 and \(-1\), eliminating the need for parallel alignment. Figure 17: The gaze sequence of driver #1 for the rectilinear segment. Figure 18: The gaze sequence of driver #1 for the curvilinear segment. Nevertheless, to ensure precise results in scenarios where the gaze or the projection of the gaze is not parallel to the road, it is essential to account for perspective by positioning the road boundary coordinates lower in the \(y\)-axis than the gaze coordinates to avoid misinterpretations of the gaze as being outside the road borders when it is inside. This proper adjustment is achieved by narrowing the selection window size in the \(y\)-axis for the road coordinates to ensure that the chosen road border coordinates are lower in the \(y\)-axis than the driver's gaze position. Another critical aspect that should be considered when analyzing gaze position at road borders is appropriately adjusting the selection window in critical situations. For instance, when the driver's gaze is near the right borderline of the road, it is imperative to adjust the selection window to an appropriate size. This is particularly important when the driver is driving counterclockwise (in right-hand drive), as the perspective can lead to an erroneous interpretation of the gaze direction. Therefore, adjusting the selection window to an optimal size under such critical circumstances is essential to ensuring an accurate interpretation of the driver's gaze. Refer to Figure 13 to better understand the selection window adjustment in critical scenarios. The difference between a counterclockwise and a clockwise circuit depends on the direction of circulation. In a right-hand circulation and a counterclockwise circuit, the driver must drive close to the roadside on the right, whereas in a left-hand circulation, he must drive close to the left roadside. The vehicle's trajectory and speed profile may be affected if the road section is wide enough (more than one lane). Curvilinear segments are generally short, and fewer frames are available for analysis. Besides this, some of them could be unusable because the road line border is not visible due to either the perspective of a curvilinear stretch or the obstruction of the door pillar (for left curves) or the windscreen pillar (for right curves). Outcomes show where the driver looks, outside or inside the road, depending on the driver's style. We can know where he is looking with a resolution limited only by perspective distortion, which cannot be controlled by our method.