## 3 Results and Analysis
### Analysis  
Furthermore, in engineering practice, construction cost is a crucial factor in the decision-making process. Table 5 presents the evaluation of the construction costs for each design. Since the specific cost will vary depending on various project conditions, it is challenging to provide a precise reference. Therefore, Table 5 provides a rough score of 1-4 based on the facility requirements of different designs, among which a higher value indicates a lower cost, which is more expected.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Improvement Ratio** & **LSI** & **PVTS** & **LRER** \\ \hline LOS-A & 7.48\% & 11.77\% & \(-\)9.08\% \\ LOS-B & 13.44\% & 16.21\% & \(-\)6.93\% \\ LOS-C & 15.78\% & 21.58\% & 6.86\% \\ LOS-D & 12.27\% & 16.84\% & 8.65\% \\ \hline \end{tabular}
\end{table}
Table 4: Total improvement ratio of the LSI, PVTS, and LRER to the CI.  
Figure 14: CE assigns weights to indicators in each scenario and scores each design. (**a**) Weight of each indicator at each LOS. (**b**) Score for each design.  
The latest CE result with construction cost taken into consideration is presented in Figure 15, which includes the weight assignment result of the entropy method for comparison to the CRITIC method. Figure 15a reveals that the entropy method focuses solely on the information and leads to a relatively even distribution of weight. On the contrary, the CRITIC method screens out the internal linkages between traffic indicators and classifies construction cost as the second category, thereby achieving a balanced view between cost and traffic performance. This also explains the rationality and scientific validity of the CRITIC method in engineering evaluation. Figure 15 and Table 6 show the final scoring results.  
In summary, CI demonstrates a competitive balance between traffic performance and construction costs, particularly at LOS-A, in which the advantages of optimization have yet to be fully realized. LSI still remains the optimal choice at LOS-B and LOS-C, while LRER becomes the preferred option at LOS-D.  
However, in reality, the proportion of diverging flows and trucks is constantly changing in the dynamic organic road traffic system. Therefore, this section proceeds to explore  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**LOS** & **CI** & **LSI** & **PVTS** & **LRER** \\ \hline A & 35.3 & 28.9 & 19.3 & 16.5 \\ B & 24.8 & 33.5 & 27.7 & 14.0 \\ C & 24.4 & 26.6 & 25.1 & 24.0 \\ D & 24.9 & 25.2 & 22.0 & 27.9 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Final score for each design from LOS-A to LOS-D with a diverging ratio of 25% and a truck proportion of 30%.  
Figure 15: Latest CE result with construction cost taken into consideration for each design at each LOS. (**a**) Weight of each indicator at each LOS, among which the outer ring denotes the entropy method result and the inner denotes the CRITIC method. (**b**) Score for each design with the CRITIC method of assigning weight.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Construction Cost** & **CI** & **LSI** & **PVTS** & **LRER** \\ \hline Segregated subgrade and barrier facilities & N/A & 2 nd & 1 st & 3 rd \\ Auxiliary Lane & 1 st & N/A & N/A & N/A \\ Ramp & 2 nd & 1 st & 1 st & 1 st \\ Score & 4 & 2 & 1 & 3 \\ \hline \hline \end{tabular}
\end{table}
Table 5: A rough score for the construction cost of each design.  
additional traffic scenarios and uses the available CE results in Figures 16 and 17. The Appendix A provides specific simulation details that support CE analysis.  
In actual engineering construction practice, the corresponding design scheme can be taken based on the design traffic volume, and in the meantime, the results of the traffic survey on the diverging ratio and truck proportion in the road network should also be taken into consideration.