## 5 Conclusions  
Traditional toll rate optimization models typically assume perfect rationality in travel behavior, often neglecting users' subjective preferences, and lack real-world toll data in multi-rate scenarios. Relying on the Netlogo6.4.0 platform, this study constructs an agent-based simulation model, innovatively incorporating factors such as individual attributes, route preferences, travel distance, toll rates, and operating speeds as inputs. By setting up a more realistic simulation environment, the research dynamically analyzes the relationships among toll rates, operating speeds, user rationality levels, toll revenue, and freeway travel demand under various simulation scenarios. This study identifies a theoretically optimal toll rate and provides a new theoretical framework and technical tools for freeway toll rate optimization.  
This research reveals that freeway travel demand declines as toll rates increase, and toll collection exhibits a \"synchronous phase\" and an \"asynchronous phase\" as toll rates increase, so we conclude that there is a theoretical toll rate range (in this study, the toll rate is CYN 0.45 per kilometer) that maximizes freeway toll collection. The effectiveness of the proposed model in accurately identifying toll rate adjustment schemes or evaluating the effectiveness of toll rate adjustments is demonstrated through a case study in Guangxi. Currently, the toll rate for Type I passenger vehicles on Guangxi's freeways is CYN 0.5 per kilometer. When a 10% discount is applied to the toll rate for this vehicle type, reducing  
Figure 11: Difference of freeway and parallel road speed and total freeway tolls.  
Figure 10: Difference in freeway and parallel road speed and freeway user share.  
it to CYN 0.45 per kilometer, the system revenue reaches its maximum value. We further observed that the \"synchronous phase\" and \"asynchronous phase\" are not symmetrical, with the \"synchronous phase\" having relatively more dramatic changes and the \"asynchronous phase\" having relatively more dramatic changes. The rationality level does not have a direct impact on toll collection, but it affects the time needed for toll collection to reach a steady state after conducting a toll rate scheme. Therefore, prior to determining the toll rate adjustment scheme or evaluating the effectiveness of the toll rate adjustment, it is necessary to fully understand the rationality level of the local freeway users and to estimate the appropriate time to evaluate the effectiveness of the implementation of the rate plan in advance. In addition, due to the competitive relationship between freeways and parallel state and provincial arterials, the higher the freeway speed and the lower the parallel road speed, the higher the freeway travel demand and toll collection. However, after the freeway speed increases to 110 km/h, continuing to raise the speed of the freeway, the promotion effect on the freeway user share and the total toll of the freeway is attenuated. Similarly, after parallel road speeds grow to 70 km/h, continuing to increase their speeds attenuates the attraction of the users traveling on the freeway, constraining the effectiveness of adopting parallel roadways to shed freeway travel demand. Furthermore, the speed difference between the freeway and the parallel road also has a certain correlation with the freeway travel demand and toll collection. When the speed difference between the freeway and the parallel road is less than 5 km/h, the widening of the speed difference will not positively promote the freeway toll collection. The results could help the government to formulate more effective transportation policies to guide rational transportation planning, improve the efficiency and sustainability of the transportation system, and balance the traffic demand and toll revenues to ensure the stability of freeway tolls while satisfying the freeway travel demand.