## 3 Results and Analysis
### VISSIM Results  
Table 3 presents the calibration results of the VISSIM model across the four investigated LOS, where the diverging ratio is about 25%, with trucks accounting for 30% of the traffic. MAPE for both capacity and density remains at acceptable levels, as previous studies have confirmed that MAPE values under 15% can provide accurate and credible guidance for engineering practice [41; 42]. Furthermore, to demonstrate the accuracy of the VISSIM model, various volumes were inputted, and the density results presented in Figure 12 align with the Greenshields model, exhibiting a 99% \(R^{2}\). This outcome indicates that the simulation matches the actual situation with fully plausible results.  
Figure 10: Time headway distribution for LOS-A to LOS-D on the LR and PVTS sections, respectively, with the range from 15% to 85% interval in the rightmost column.  
The simulation results for the four investigation scenarios are depicted in Figure 13. The analysis shows that under LOS-A and LOS-B, LSI and PVTS significantly improve CL Although PVTS has a lower mainline speed than LR at this LOS and its potential for exit diverging area has not been completely utilized, it still provides a significant improvement in overall performance. On the other hand, LRER failed in all aspects of the competition with CI. This can be explained by the fact that the significant speed dispersion produced in the diverging area on the fast lane of the left contributes to more conflicts and congestion at that LOS, and this issue cannot be resolved by reducing lane changes.  
Figure 11: Investigate vehicle lane change execution characteristics. (**a**) Each line denotes a vehicle’s lane change trajectory. X denotes the time series of lane changing with 0 marked as the moment when the vehicle centerline coincides with the boundary of the fast and curb lane, and Y denotes the width of lane changing with 0 marked as the same means. (**b**) A moderately strong positive correlation has been shown between length and speed, with a Kendall coefficient of 0.326. Each point denotes the data for a lane change.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Flow**} & \multicolumn{2}{c}{**LOS-A**} & \multicolumn{2}{c}{**LOS-B**} & \multicolumn{2}{c}{**LOS-C**} & \multicolumn{2}{c}{**LOS-D**} \\ \cline{2-9}  & **T** & **D** & **T** & **D** & **T** & **D** & **T** & **D** \\ \hline Investigated Capacity (veh/h) & 2201 & 704 & 3379 & 1099 & 4811 & 1511 & 5681 & 1924 \\ Simulated Capacity (veh/h) & 2209 & 691 & 3353 & 1089 & 4708 & 1499 & 5434 & 1815 \\ Individual MAPE (\%) & 0.36 & \(-1.85\) & \(-0.77\) & \(-0.91\) & \(-2.14\) & \(-0.79\) & \(-4.35\) & \(-5.67\) \\ MAPE (\%) & \(-0.17\) & & \(-0.80\) & & \(-1.82\) & & \(-4.68\) \\ \hline Investigated Density (veh/km) & 27.75 & & 43.21 & & 63.60 & & 80.92 \\ Simulated Density (veh/km) & 27.59 & & 43.22 & & 63.06 & & 80.77 \\ MAPE (\%) & \(-0.57\) & & 0.02 & & \(-0.86\) & & \(-0.19\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: MAPE of the calibration at the four LOS, where T denotes through traffic and D denotes the diverging flow.  
Figure 12: VISSIM simulation input results of density under different volumes, where colored dots denote result data, and the pink curve denotes the fit function to these data that matches the theoretical Greenshields formula, which is denoted with a gray dash.  
However, significant changes have occurred under LOS-C and LOS-D, with LRER regaining the lead over CI, while PVTS has topped the radar plot in comprehensive performance. Despite this, LSI continues to exhibit better performance than LRER, which again confirms the advantage of the right-side exit ramp over the left, as is the commonly accepted conclusion in the vast majority of studies. Another fact that has emerged is that multiple lane changes preceding the exit ramp still struggle to accommodate heavy traffic, and the barrier effect from trucks cannot be neglected, particularly in this scenario.