# Characterization of Driver Dynamic Visual Perception Under Different Road Linearity Conditions
## 5 Conclusions  
In this study, the following main conclusions were drawn from the real-vehicle tests and data analysis of the eye tracking characteristics of 23 drivers on different road sections including straight line, curved road, climbing, and downhill:  
1. The article revealed the significant effects of different roadway driving tasks on drivers' eye tracking characteristics and clarified the regular changes of the three indicators of eye tracking characteristics describing the eye movement behaviors of fixation, pupil, and sweep under different roadway conditions. The average fixation duration ranking was found to be straight ahead > climbing > downhill > turning, that of pupil diameter was found to be turning > downhill > climbing > straight ahead, and that of saccade amplitude was found to be downhill > turning > climbing > straight ahead. These results reflected the profound influence of driving task complexity and environmental dynamics on drivers' visual behavior. 2. Drivers' eye tracking characteristics showed significant variability under different roadway driving tasks. One-way ANOVA results showed statistically significant differences in average fixation duration, pupil diameter, and saccade amplitude under different roadway conditions (\(p<0.05\)). This study provides an important experimental basis for driving behavior modeling, driver state monitoring, and advanced driver assistance system (ADAS) optimization. 3. A computer-fitted model of driving time and eye tracking indicators was developed. Based on the experimental data, this paper established a computer-fitted model between driving time and eye tracking indexes, which further revealed the law of visual task allocation of drivers under different road sections. The model was able to quantitatively describe the time-varying characteristics of average fixation duration, pupil diameter, and saccade amplitude of drivers under different road sections and provided theoretical support for the optimization of future traffic safety interventions and advanced driver assistance systems. In summary, this study, through the systematic analysis of a driver's visual characteristics, using statistical methods to verify the differences of the driver's eye tracking characteristics under different road conditions, and through the computer fitting method, quantitatively describes the change rule of the eye tracking characteristics of different road sections, which provides a scientific basis and an important reference for the optimization of road design, traffic safety management, and intelligent transportation systems. However, this study also has some limitations. For example, the sample size of subjects is relatively small, which may not be able to fully reflect the diversity of different driving groups; the selected eye tracking indexes are relatively single and fail to fully integrate other potential key indexes (e.g., the distribution of fixation points and fixation duration), and only a one-way ANOVA was performed; however, considering that factors such as individual driver differences and driving task complexity may interact on eye tracking behavior, subsequent studies will use a two-way ANOVA approach to comprehensively assess the interaction between road conditions and these factors; at the same time, in constructing the eye tracking models under the four road sections, we mainly focused on the characteristics of the changes in the temporal dimension and did not fully take into account the complexity of the spatial environment and the influence of the physiological and individual differences of different drivers. The cubic polynomial model performs well in the fitting effect, but it is a relatively complex model and subsequent studies can explore the use of more simplified models.