## 5 Results and Discussion
### Comparison of Traffic Conditions in the Merge Bottleneck Area  
In the study, the primary cause of road congestion is the emergence of bottlenecks at the on-ramp merge points, which subsequently spread to upstream areas. Therefore, a comparative analysis of the traffic conditions for the overall road and the bottleneck areas was conducted. Figure 9 shows the spatiotemporal density variation of the overall mainline traffic, where Lane 1 represents the lane adjacent to the on-ramp. It can be observed that in the no-control scenario, the convergence of traffic from the on-ramp leads to congestion before the on-ramp, which then spreads to the upstream road sections and adjacent lanes. Under the SPSC-LCC strategy, the congestion in the control area before on-ramps is significantly alleviated; however, some congestion still occurs in the upstream area. In contrast, under the FM-ITC and FM-ITC-Darea control strategies, the integrated control method imposes speed limits on the upstream traffic flow and directs vehicles within the control area to move preferentially toward the inner lanes. This reduces the density of the outer lanes and increases the utilization of the inner two lanes. Overall, the spatiotemporal impact of traffic congestion caused by the bottleneck spread is significantly reduced. Figures 10 and 11 provide a more detailed analysis of the bottleneck traffic conditions at two on-ramps (i.e., cells 7 and 14). Due to the convergence of traffic from the on-ramps, the density of the outer lanes (i.e., Lane 1) at both on-ramps exceeds the critical density in the no control scenario, affecting the downstream traffic flow. The traffic fluctuations are more pronounced at cell 14 due to the presence of upstream on-ramps. By observing the simulation results of the three control strategies, it is evident that integrated control tends to eliminate traffic bottlenecks in the outer lanes. Although this increases the traffic load on the inner lanes (particularly Lane 2) by directing lane changes, the local objectives are achieved. This approach mitigates the negative impact of merging traffic to some extent and stabilizes the fluctuating traffic flow at cell 14. Given these observations, it can be seen that the SPSC-LCC strictly adheres to its logical settings, aiming to regulate each lane within the control range to the desired density and flow state. However, this setting sometimes has adverse effects on roads outside the control range (e.g., causing new traffic congestion). Figure 8: TTS convergence curves for FM-ITC-Darea training processes. Figure 9: Overall spatial–temporal density of each lane of the mainline under different strategies, where (**a**) denotes the no control scenario, (**b**) denotes the SPSC-LCC strategy scenario, (**c**) denotes the FM-ITC strategy scenario, and (**d**) denotes the FM-ITC-Darea strategy scenario. Compared to the SPSC-LCC strategy, the FM-ITC and FM-ITC-Darea control strategies have a more flexible perception of road traffic conditions, enhancing the effectiveness of control commands and reducing traffic fluctuations caused by control commands lagging behind actual traffic conditions. FM-ITC-Darea exhibits similar effects to FM-ITC in controlling local traffic, but has the added advantage of determining the control area. This means it is not limited to achieving control objectives for the outer lanes but is more inclined to optimize traffic conditions within the entire effective bottleneck range of the on-ramps. Figure 10: Changes in mainline density in ramp merging areas under different integrated control strategies, where (**a**) denotes the no-control scenario, (**b**) denotes the SPSC-LCC strategy scenario, (**c**) denotes the FM-ITC strategy scenario, and (**d**) denotes the FM-ITC-Darea strategy scenario. Table 2 presents the overall evaluation metrics under different control strategies. According to the simulation results, compared to the no-control scenario, the SPSC-LCC strategy is less effective in alleviating congestion.