## 3 Results and Analysis  
### Data Collection and Processing  
The data collection for this study has been planned to occur at several sections approaching exits on the eight-lane G30 and G65 national expressways, which serve as critical traffic arteries in Shaanxi Province, China. These sections are comprised of a four-lane main-line and a two-lane ramp in each direction with design speeds of 120 km/h and 60 km/h, respectively. Prior to the investigation, the AMAP platform was used to determine the investigation period of various LOS with congestion delay indexes in the vicinity of Xi'an, as shown in Figure 7. Table 2 contains some fundamental information about the surveyed section, while Figure 8 displays geographical locations and actual views. Figure 8: Geographical location and actual view of the investigated section and interchanges. A and B denote Interchange Xiwu and Interchange Epanggong on G30, respectively, while C denotes Interchange Xiuq on G65\({}_{22}\). In addition, G30 and G65\({}_{22}\) are traced in orange and blue, respectively. Figure 7: Average congestion delay index for a week around Xi’an. The data collection in this study will focus on several significant traffic situations, specifically from LOS-A to LOS-D, which represent the majority states of the surveyed expressway. Figure 9 shows vehicle speed distribution at the four LOS, which will serve as a critical parameter in the development and calibration of the VISSIM model. Additionally, Figure 10 illustrates the time headway, which is another calibration parameter. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Interchange**} & \multirow{2}{*}{**Expressway**} & \multicolumn{2}{c}{**Design Speed (km/h)**} & \multirow{2}{*}{**Management**} \\ \cline{3-3} \cline{5-5}  & & **Mainline** & & **Ramp** \\ \hline Xiwu & G30 & 120 & 60 & LR \\ Epanggong & G30 & 120 & 60 & LR \\ Xinqu & G6522 & 120 & 60 & PVTS \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Basic information of the investigated section and interchanges. Figure 9: Cumulative distribution curve for vehicle speed at LOS-A to LOS-D with LR and PVTS management strategies, respectively. \(V_{85}\) is also labeled in the legend. (**a–d**) denote the first to the fourth lane, left to right, respectively. The message conveyed in Figure 9 tends to suggest that there is no significant difference in speed distribution between the LR and PVTS on the basic section prior to the interchange. However, subtle variances can still be observed in the following ways:  
* On passenger vehicle lanes, PVTS displays marginally slower vehicle speeds than the LR in smooth traffic conditions. However, as the LOS decreases, the PVTS regains its advantage, particularly noticeable on the curb lane. * On truck lanes, the fast lane shows a similar trend to the aforementioned, while PTVS exhibits an advantage in the curb lane. This phenomenon can be explained by the fact that certain slow-moving vehicles, or \"turtle cars\", occupying the mixed lane have shifted to the passenger vehicle lane, producing a negative impact. Although this impact is negligible at low LOS, as all vehicle speeds will be suppressed, it is evident in the figure that the number of \"turtle cars\" on PVTS truck lanes is fewer than that on LR mixed lanes. After excluding this effect, the benefits of PTVS in mitigating the barrier effects produced by trucks can still be interpreted. The same explanation still applies to the clarification for Figure 10.  
Lane changes are the most significant vehicle behavior in expressway diverging areas, involving two steps: gap queuing and acceptance and lane change execution. The VISSIM model typically defaults to a lane change execution length of 200 m. However, in practice, that will be influenced by various factors, such as speed, driver experience and style, and urgency. Thus, the authors conducted a dedicated investigation for calibration.