## 3 Data Collection
### Experimental Data  
The experiments employed the SmartEye Pro eye-tracking system to capture the visual behaviors of drivers interacting with blind spot images during lane changing. This system is equipped with four gaze-tracking cameras, which capture the dynamic gaze of the drivers, while a foreground wide-angle camera records the frontal scenery during driving. Utilizing the accompanying Human Research Tool (HRT) software, the foreground video and gaze data of the drivers are synthesized to obtain metrics such as fixation points, gaze heights, and head rotation angles. The data collected from the two sets of experiments are encompassed in Table 1, and detailed information about traffic flow levels and vehicle parameters is shown in Figure 6, Tables 2 and 3. Figure 4: The route for Experiment 1 and Experiment 2. Figure 5: Three blind zone positions of Vehicle Type 1 in Experiment 2 (from **left** to **right**: position 1, position 2, and position 3). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Center Screen**} & \multicolumn{3}{c}{**Blind Zone Image**} & \\ \cline{2-9}
**Vehicle Type** & \begin{tabular}{c} **Length** \\ **/cm** \\ \end{tabular} & \begin{tabular}{c} **Width** \\ **/cm** \\ \end{tabular} & \begin{tabular}{c} **Area** \\ **/cm** \\ \end{tabular} & \begin{tabular}{c} **Length** \\ **/cm** \\ \end{tabular} & \
\begin{tabular}{c} **Width** \\ **/cm** \\ \end{tabular} &
\begin{tabular}{c} **Area** \\ **/cm** \\ \end{tabular} & \(\rho\) & **D/cm** \\ \hline
1 & 33.1 & 20.7 & 685.2 & 12 & 6.1 & 73.2 & 0.11 & 21.2 \\ \hline
2 & 65.8 & 10.9 & 717.2 & \begin{tabular}{c} L: 10.9 \\ \end{tabular} & \begin{tabular}{c} L: 98.1 \\ \end{tabular} & \
\begin{tabular}{c} L: 0.14 \\ \end{tabular} &
\begin{tabular}{c} L: \(-14.5\) \\ \end{tabular} \\ \hline
3 & 21.8 & 23.9 & 521 & 12.2 & 7.2 & 87.8 & 0.17 & 38.0 \\ \hline \hline High & & & & & & & \\ \hline \end{tabular}
\end{table} 
Table 1: Indicators of the collected data. \begin{table}
\begin{tabular}{c c} \hline \hline
**Indicator** & \multicolumn{3}{c}{**Explanations**} \\ \hline Gaze Landing Point Coordinates & \begin{tabular}{c} Taking the upper left corner of the HRT’s foreground video as the origin, the horizontal and vertical pixel distances corresponding to the driver’s gaze are output. These are used in the calculation of the time buffer value within the AttenD algorithm. \\ Head Rotation Angle \\ Eye Height \\ Traffic Flow Level \\ Road Type \\ Lane Change Direction \\ \end{tabular}  & \ \begin{tabular}{c} Taking the upper left corner of the HRT’s foreground video as the origin, the horizontal and vertical pixel distances corresponding to the driver’s gaze are output. These are used in the calculation of the time buffer value within the AttenD algorithm. \\ The left–right head rotation angles captured by the eye-tracker, which serve as auxiliary data for the calculation of the time buffer value. \\ The z-axis coordinate of the driver’s gaze origin position, as output by the eye-tracker in the world coordinate system. \\ Based on the volume of vehicles ahead on the road, traffic flow is classified into three levels: high, medium, and low. An example of traffic flow levels is illustrated in Figure 7. \\ Road Type \\ Lane Change Direction \\ Vehicle Type \\ \end{tabular}  &
\begin{tabular}{c} The type of road where the vehicle was located during data collection, categorized as city roads or expressways. \\ The direction of lane change (left or right) corresponding to each data entry. \\ As mentioned in Section 4.1, the vehicle type was analyzed as an overall variable to examine its impact on cognitive load in Experiment 1. Relevant parameters of the three vehicle types are presented in Table 2, where \(\rho\) represents the ratio of the blind zone image to the center screen and D represents the horizontal distance from the left end of the blind zone image to the center of the steering wheel.