## 3 Driver Behavior Simulation
### Driver Workload Measurement and Results  
Scholars have discovered that driving induces various loads [31]. Excessive or insufficient driver workload negatively impacts driving safety and efficiency. Optimal driving performance is achieved only within a reasonable workload range. Studies [32] have highlighted three primary methods employed for evaluating driver workload. 1. Subjective Measurement  
The NASA Load Index (NASA-TLX) scale is employed as the evaluation criterion for subjective measurement. Sixteen NASA-TLX scales and six-dimensional weight comparison cards were obtained. Utilizing the original scores and weights of the six load dimensions, Equation (9) is applied to calculate the subjective driving workload values of the subjects. \[W_{a}=\frac{\sum\limits_{i=1}^{6}W_{i}M_{i}}{\sum\limits_{i=1}^{6}W_{i}} \tag{9}\]  
The subjective driving workload values of the subjects are shown in Table 4.  
Figure 10: Driver comfort survey results. * The weightings assigned to the three load dimensions--mental demand, time demand, and effort, are notably substantial, indicating elevated demands on drivers' cognitive faculties, decision-making skills, and attentiveness caused by RTRL. Simultaneously, ensuring optimal driving efficiency within RTRL necessitates the application of relevant design parameters and signage placement, enabling drivers to have sufficient reaction time for operations. * The majority of subjects exhibit higher workload values, confirming the escalated complexity involved in the driving task within RTRL. * Task Performance Measures  
Vehicle speed serves as an intuitive indicator of the impact of the road environment on driver performance. A higher vehicle speed indicates favorable road conditions. Thus, vehicle speed was utilized as a task performance indicator. The UC-win/Road simulation software recorded the vehicle speed, as shown in Figure 11.  
There is a notable decrease in vehicle speed before the diversion area and at approximately 800 m from the diversion nose (at 3100 m), which prompts subjects to execute the driving task smoothly and calmly. Around 400 m from the diversion nose, a slight vehicle speed increase of 5-8 km/h is observed, which indicates that having clarified the driving direction, subjects began to incrementally increase their speed. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Participant**} & \multicolumn{6}{c}{**Raw Scores \(M_{i}\)/Weight \(W_{i}\)**} \\ \cline{2-8}  & **Physical** & **Spiritual** & **Time** & **Operational** & **Effort** & **Frustration** & **\(W_{a}\)** \\  & **Need** & **Needs** & **Requirement** & **Performance** & **Effort** & **Level** & \\ \hline
1 & 20/0 & 60/2 & 80/5 & 80/4 & 70/3 & 30/1 & 72 \\
2 & 10/0 & 75/4 & 75/5 & 50/3 & 25/2 & 25/1 & 60 \\  
Physiological Measurements  
The pupil diameter was chosen as the evaluation index for the physiological measurement method. Subjects' pupil diameter data were collected using the SMI ETGTM spectacle-type eye-tracking device. BeGaze 3.6.52 analysis software processed the pupil diameters of the subjects in each driving scenario to ascertain the characteristics of their pupil diameter variations. Larger amplitude fluctuations and more frequent pupil diameter fluctuations indicated higher physiological driving loads among the subjects. The changes in the subjects' pupil diameter data are shown in Figure 12.  
Figure 12: Changes in pupil diameter in some subjects. Subjects generally exhibited small pupil diameters, with most displaying an increasing trend and heightened fluctuations in pupil size near the exit (corresponding to a period of 80,000 to 120,000 ms). This suggests that making choices regarding diversion directions in the exit area significantly escalates the mental and physiological loads experienced by drivers. To efficiently perceive overhead road sign information within a constrained time frame, subjects needed to widen their pupil diameters to gather more road-related data.