## 6 Results  
This study provides a high-level evaluation model for service providers, focusing on the resources required per cell to support a maximum number of users without delving into specific underlying technologies used for optimizing operating frequencies. In our use case, a user is defined as a driver utilizing a VFH application on their cell phone, requiring a specific frequency to establish a connection with the serving cell. This abstraction, facilitated by network slicing, is pertinent for provisioning 5G services where understanding the overall infrastructure capacity to support advanced services is prioritized over detailed technical characteristics. This section presents the results obtained from the MMtQHU model in the Ingolstadt traffic scenario, evaluating the impact of human uncertainty on resource allocation in 5G networks and on the quality of service measured through the CDR. Simulations were conducted for two vehicle load levels (5% and 10% of vehicles using VFH applications), and different frequency allocation methods, e.g., nearest integer rounding, standard rounding, and ceiling rounding, were tested during three congestion periods (HC1, HC2, and HC3). In the simulated scenarios with optimal routes (excluding deviations due to human uncertainty), the results indicate that the CDR remained within the acceptable threshold of 1% across all congestion periods for both 5% and 10% vehicle loads. As shown in Figure 5, even during peak congestion periods, the system maintains quality of service by adhering to the CDR threshold, suggesting that allocating 12 frequencies per cell is sufficient to handle the simulated traffic levels under optimized routing conditions. Figure 6 illustrates the total number of frequencies allocated across the 10 evaluated cells during the three congestion periods, comparing the rounding, ceiling, and nearest methods. In all scenarios, the ceiling method consistently allocates a higher number of frequencies than the nearest method, with differences ranging from 2 to 18 additional frequencies per cell. This demonstrates that the nearest method is more conservative in resource allocation, providing an added margin of safety in high-demand situations. However, both methods result in a lower total frequency allocation compared to the ideal scenario of 12 frequencies per cell (120 total frequencies), highlighting the need for further optimization in resource management. Figure 7 presents the CDR for the three peak congestion periods evaluated under VFH load levels of 5% and 10% using optimal routing. Frequencies were allocated using the  
Figure 5: CDR for optimal routing with 12 frequencies per cell during peak congestion periods. nearest rounding method, chosen for its efficiency in minimizing resource usage. The results indicate that, despite the reduced frequency allocation, the CDR consistently remains below the critical 1% threshold across all congestion scenarios. This demonstrates that the nearest rounding method satisfies the required performance criteria, ensuring service reliability even under high traffic conditions with limited resource allocation. These findings underscore the method's viability in maintaining network quality while optimizing resource utilization in 5G environments. Figure 8 illustrates the negative impact on system performance caused by the introduction of alternative routes that deviate from the predefined paths suggested by the VFH application. This degradation is primarily attributed to insufficient resource allocation per cell, which is inadequate for addressing the dynamic demands introduced by route deviations. Notably, the HC2 period under a 5% VFH load shows less pronounced degra  
Figure 6: Total frequency count by rounding method in optimal routing scenarios. Figure 7: CDR results with nearest rounding in optimal routing scenarios. dation, indicating marginally better adaptation to traffic variability.