Simulation Study on Freeway Toll Optimization Considering Bounded Rationality and Dynamic Relationships Among Toll Rates, Travel Demand, and Revenue

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.