## 4 Discussion  
Generally, drivers engage in a visual search to find out the road conditions and traffic situations, and to avoid any potential hazards, but novice or older drivers with low cognitive ability may be involved in a car accident as they repeat the process of examining the same object to have an accurate assessment of it or an AOIs, or obtain insufficient information due to inadequate visual search. The current study aimed to propose a method to differentiate at-risk drivers who are highly likely to cause an accident by conducting static and dynamic analyses on gaze and comparing the information obtained from the visual search depending on the levels of driving experience. The indicators used for the  
Figure 8: The transition matrix of drivers’ gaze from one AOI to the next. (**a**) novice driver; (**b**) experienced driver. \begin{table}
\begin{tabular}{l c c c c} \hline \hline  & \multicolumn{2}{c}{**Novice**} & \multicolumn{2}{c}{**Experienced**} \\ \cline{2-5}
**Area of Interests (_i_)** & **Freq. (_n_)** & **Probability (_P\({}_{i}\)_)** & **Freq. (_n_)** & **Probability (_P\({}_{i}\)_)** \\ \hline Traffic lights & 572 & 0.12 & 484 & 0.10 \\ Pedestrian signal light & 0 & 0 & 683 & 0.13 \\ Pedestrian & 224 & 0.05 & 297 & 0.06 \\ Passing vehicle & 643 & 0.13 & 286 & 0.06 \\ Navigation system & 683 & 0.14 & 253 & 0.05 \\ Rear-view mirror & 143 & 0.03 & 637 & 0.12 \\ Side mirror (Left) & 167 & 0.31 & 727 & 0.15 \\ Side mirror (Right) & 0 & 0 & 344 & 0.07 \\ Dashboard & 794 & 0.16 & 290 & 0.06 \\ Others & 1747 & 0.35 & 980 & 0.20 \\ \hline
**Total** & 4973 & 1 & 4981 & 1 \\ \hline
**SGE** & \multicolumn{2}{c}{**2.60**} & \multicolumn{2}{c}{**3.09**} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Probability distribution by area of interest and SGE. static analysis on gaze included dwell time, fixation duration, and the number of fixation and SGE, whereas the dynamic analysis adopted GTE. The driving performance assessment was carried out using a VR driving simulator based on a scenario involving an intersection where visual properties were abundant. The static analysis of gaze indicated that for the dwell time, the novice group tended to hold their gaze at a certain AOI for a long time, which means that they spent a long time on searching the driving route and dangerous elements. Meanwhile, the experienced group displayed a relatively even distribution, signaling that they spent time on surveying the overall surrounding traffic situations on the road they were on. In terms of fixation duration, the novice drivers displayed a longer duration than the experienced driver, spending the longest time on observing the left side and rear-view mirrors. In other words, they spent a long time on gauging the distance between their vehicle and those behind and on the sides. In addition, the experienced group had a short fixation duration on average, but they spent the longest time on the traffic lights for pedestrian, which could be understood as their attempt to predict the next traffic light signal. When it comes to the frequency of fixation, the most frequently checked AOIs by the novice group when they made a right turn at an intersection were the passing vehicles and pedestrians. By contrast, the experienced drivers looked at the right- and left-side mirrors more frequently than the others. In other words, the novice group tended to look what was before them repeatedly, while the experienced group was more likely to survey the AOIs on their right and left sides more frequently. The estimates of SGE indicated that the experienced group processed a larger amount of information than the novice and recorded a high entropy due to low gaze density as they drove while giving similar visual attention to the entire AOIs.