## 4 Discussion  
From the perspective of the methodology, despite the fact that the VISSIM microsimulation model calibrated with traffic data basically recreates the real traffic scenario and provides accurate node evaluation, it is still difficult to support an accurate overall evaluation of the design schemes solely based on the single VISSIM results in Figure 13 and Appendix A, which can only provide a general basis for judgment. Meanwhile, the introduction of the CRITIC method improves that, referring to Tables 4 and 6, and  
Figure 16: Comprehensive performance evaluation and comparison for each of the four designs in dynamic traffic. The X and Y axes denote diverging ratio and truck proportion, respectively, between 20% and 30% and 25 and 35%, and the Z axis denotes the four design schemes. Specific scores can be acquired with color mapping. (**a**) LOS-A. (**b**) LOS-B. (**c**) LOS-C. (**d**) LOS-D.  
Figure 17: Optimal solution under different traffic conditions. Blue blocks denote CI, green blocks denote LSI, yellow blocks denote PVTS, and orange blocks denote LRER. Figures 15-17. Based on that, not only the comprehensive traffic performance of the scheme can be accurately and quantitatively evaluated, but also other factors such as the construction cost and consumption of the scheme can be taken into consideration, which is conducive to the comprehensive judgment of the sustainability of schemes and substantially improves the efficiency and accuracy of engineers' decision-making. The comparison of the weight assignment results between the CRITIC method and the entropy method also clarifies the advantages of the CRITIC method for efficient and accurate application in the transportation field, referring to Figure 15 and its analytical description. From the perspective of the results, according to Figure 16, the results consistently demonstrate that CI outperforms other designs at LOS-A. This can be attributed to the fact that, in smooth traffic, vehicles remain free to change lanes without excessive restrictions, resulting in an acceptable level of extra conflicts and delays associated with consecutive lane changes in diverging areas. Thus, the benefits cannot be matched by the massive renovation required in this condition. Similarly, the same reasoning applies to LSI and PVTS, although PVTS performs best in traffic indicators at LOS-A. LRER deservedly performs the worst due to its unsatisfactory transport performance, as well as maintaining this tendency up to LOS-B, and the explanation has already been discussed in Section 3.2. LSI and PVTS become dominant below LOS-A, with the most pronounced dominance occurring between LOS-B and LOS-C. That indicates that reducing lane changes would achieve the best benefits as traffic converges and lane changes become more limited. From a transportation standpoint, PVTS makes significant sense for relieving the barrier effect from trucks at low LOS, although LSI may be the better choice when construction costs are considered. Subsequently, as the volume increases, the mainline traffic switches from stable flow to congested flow with LOS-D reached, which means the reaching of mainline capacity bottlenecks, which restrains the optimized design from accessing the desired efficiency. At this point, LRER profits from the less prominent mainline speed inferiority of the left-side exit ramp, highlighting its competitiveness due to lower construction requirements than LSI. It appears that the diverging ratio always has a positive correlation with congestion and conflict, especially at lower LOS, but does not produce an excessive substantive impact on scheme choice. From a microscopic perspective, the success probability of a lane change depends on the time headway on the target lane. Thus, more diverging will take up more space on the curb lane and increase density, which serves as the mechanism to create more congestion and conflicts.