## 4 Simulation Experiments
### Analysis and Results
#### 4.2.2 Analysis of Coordinated Through-Direction Performance Capacity  
The analysis focuses on the numerical values and changes in the coordinated through-direction traffic capacity of the controlled group relative to the uncontrolled group, as shown in Figure 10. It can be observed that the numerical values of the through-traffic capacity in the experimental group and the control group are similar, and their fluctuation patterns are consistent. SPSS was used to perform the Mann-Whitney U test, and the results indicate \(P=0.938>\alpha=0.05\). The analysis reveals that there is no significant difference between the two groups of experimental data, demonstrating that the multi-strategy combined optimization method has no significant impact on the traffic capacity of the coordinated through direction.  
Figure 8: Comparison of downstream intersection capacity control effects.  
After applying coordinated control strategies to both transition types, the average vehicle delay time significantly decreases for most combinations of influencing factors, indicating a noticeable optimization effect, as shown in Figure 11.  
For an L-S cycle transition, the optimization ratio of average vehicle delay time in the controlled group relative to the uncontrolled group fluctuates significantly, ranging from 0 to \(-40\%\) overall. In particular, in the scheme combinations number 14, 18, and 22, the optimization effects are relatively good. However, in the scheme combinations number 6, 8, 12, 15, 16, and 19, the optimization effects are relatively poor, and the reduction ratio is negative. An analysis reveals that the scheme combinations with better optimization effects have a cycle length difference of 10 s, while the ones with poorer optimization effects have larger cycle length differences, such as 40 s or 50 s. This is because when the difference in cycle lengths between upstream and downstream intersections is larger, the cycle length at the downstream intersection becomes shorter. This reduces the optimization space for dynamic phase adjustment and green extension for coordinated phases at the downstream intersection. As a result, the coordinated control strategy is less effective. Conversely, when the cycle length difference is smaller, the coordinated control effect becomes more significant.  
Figure 11: Comparison of the control effects on the average vehicle delay time in the coordinated through direction.  
Figure 10: Comparison of the control effects on the capacity of the coordinated through direction.  
For an S-L cycle transition, the optimization ratio of average vehicle delay time in the controlled group relative to the uncontrolled group tends to stabilize. Generally, it falls within the range of 15% to 55%. Compared to the L-S cycle transition, the optimization effect is more prominent in this case. In particular, the scheme combination numbers 21, 22, 23, 24, and 25 exhibit relatively good optimization effects, while numbers 15, 18, and 20 show relatively poor optimization effects. An analysis reveals that the scheme combinations with better optimization effects in the former case have an inflow traffic volume of 3000 pcu/h, indicating that the proposed coordinated control strategy is more effective in optimizing high-flow conditions in this transition type. In contrast, the scheme combinations with poorer optimization effects in the latter case have desired speeds ranging from 50 km/h to 55 km/h. The reason for this result is that when the desired speed is lower, it is not conducive to implementing the speed guidance strategy in the coordinated control optimization method. This leads to the inability of the through-arriving queue to catch up with the queued vehicles ahead promptly, resulting in the waste of phase green time and an increase in the number of through-arriving vehicles waiting.