###### Abstract  
As an essential component of China's comprehensive transportation network, freeways play an irreplaceable role in promoting regional economic integration, improving logistics efficiency, and serving public travel. However, the development of freeways faces challenges such as the underutilization of road resources, significant financial pressure for construction and maintenance, and imbalanced revenue and expenditure leading to heavy debt burdens, which severely impact the sustainable development of freeways. Optimizing freeway toll rates is an effective measure to alleviate these issues, playing a crucial role in enhancing the operational efficiency of the road network and increasing the revenue of freeway operating enterprises. Existing studies have focused on finding the optimal toll rates for freeways based on bi-level programming models, neglecting the dynamic relationships among individual travel behavior preferences, toll rates, travel demand, and toll revenue. Grounded in bounded rationality theory, the research employs microscopic traffic simulation technology to analyze the dynamic relationships among freeway toll rates, travel demand, and toll revenue. The results confirm that travel demand decreases as toll rates increase, while toll revenue exhibits asymmetric \"synchronization\" and \"asynchronization\" phases, peaking at CYN 58.9 thousand (USD 8246) when the toll rate reaches CYN 0.45/km (USD 0.06/km). Additionally, users' rationality levels significantly affect the stabilization time of toll revenue, and the speed difference between freeways and parallel roads demonstrates a threshold effect on travel demand and revenue. These findings provide theoretical and technical support for optimizing freeway toll strategies, enhancing operational efficiency, and promoting sustainable transportation development. fontsize,  
of links have flow and capacity factors below 0.33, making localized congestion during holidays a common occurrence. Secondly, there is a significant financial strain on highway operations, with a current funding gap of approximately CYN 300 billion in China's road network [3,4]. Leveraging economic levers for traffic demand management is an effective approach to mitigate the aforementioned issues. In the context of highway transportation, the economic lever refers to highway tolls, where the toll rate directly influences user travel costs, thereby adjusting the overall traffic demand and affecting the operational revenue of the highway system. Conducting targeted research on highway toll rate optimization is a crucial means to optimize traffic flow distribution within the road network and promote the efficient utilization of road resources. This approach provides methodologies for implementing differentiated highway toll schemes, traffic guidance within the road network, and variable information dissemination. It holds significant theoretical and practical value for enhancing the operational benefits, efficiency, and service levels of freeways. This study comprehensively considers multiple factors, including the socio-economic attributes of freeway users, route choice preferences, travel distance distribution, toll rates, and design speeds, to design an agent-based simulation model, simulation parameters, and update mechanisms. By adjusting the input variables, this study analyzes the changes in total system revenue and user proportions under various scenarios. This research aims to investigate the dynamic relationships among toll rates, travel demand, and revenue, which can effectively address issues such as insufficient evaluation data before and after adjustments to freeway toll policies across multiple scenarios, as well as the lack of numerical validation of these relationships. It analyzes the impacts of various factors, including toll rates, travel speeds, and levels of rationality, on freeway travel demand and toll revenue.