## 3 Methodology  
Microscopic traffic simulation is an important research method used to help understand the formation mechanism of traffic flow distribution and congestion by simulating users' behaviors of route selection on freeways and to provide a basis for the establishment of traffic demand management strategies. As a major part of microsimulation, agent-based simulation enables the establishment of behavioral decision-making models for the interaction between the agents and the environment and controls the complex behavior of agents by adjusting the simulation parameters to study the behavioral decision-making mechanism and the set of behavioral characteristics of individuals under different environments and strategies. NetLogo6.4.0 provides an intuitive interface and a simple programming language to support the modeling of multi-agents, which can easily simulate complex interactions between agents, making it easy to create agents' simulation models, and its powerful visualization function can help users to intuitively observe the behavior of agents and the interaction with control parameters. In addition, NetLogo6.4.0 has a large user community and a rich resource library for rapid modeling to accelerate the research process. Accordingly, combining the deficiencies of existing research, this study builds a simulation model of freeway toll rate, travel demand, and toll revenue based on Netlogo6.4.0, an open-source simulation platform for agents. Leveraging one month (June 2023) of toll collection data from the Guangxi Zhuang Autonomous Region's freeway network--comprising 13.8 million toll records, which analyze key indicators such as vehicle travel frequency, average travel distance, travel duration, travel speed, and the most frequently used entry and exit points as individual travel behavior characteristics--this method analyzes the correlation between the three through simulation. The specific simulation technical route is shown in Figure 1.  
The simulation model architecture is as follows:  
Step 1: Set basic parameters of the simulation system, as follows:  
- Freeway toll rate (charge rate, CR);  
- Time value (TV);  
- Rational level of the population (RLP);  
- Preference reward decay (PRD);  
- Design speeds of the freeway and parallel national/provincial roads (speed of freeway, SF; speed of other roads, SOR). Step 2: Define the population information, as follows:  
- Personal social-economic features (PSEF, as determined by user travel behavior survey questionnaire);  
Figure 1: Simulation technical route. Personal travel distance distribution (PTDD, as determined through freeway toll records);  
Travel route preference (TRP, as determined by user travel behavior survey questionnaire). Step 3: Select rational routes for each individual, as follows  
Determine the travel distance (TD) for the current trip based on PTDD;  
Calculate the travel costs for the freeway and parallel national/provincial roads (cost for freeway, CF; cost for other roads, COR) based on SF, SOR, TV, and CR;  
Compare CF and COR to determine the route in ration (RIR). Step 4: Select travel routes for each individual, as follows:  
Determine the preferred route (route in preference, RIP) based on TRP;  
Determine the final selected route (route in actual, RIA) based on RIP, RIR, and RLP. Step 5: Aggregate freeway travel demand and revenue and update individual attributes, as follows:  
Calculate the number and proportion of travelers, travel mileage, and total revenue of the freeway system based on RIA, TD, and CR for both the freeway and the parallel national/provincial roads. Update TRP based on RIP, RIA, and PRD. Step 6: Repeat steps 3 to 5. First, initialize the fundamental attributes of the agents, including income (Inc), travel distance (Dis), and route preference (P). In particular, according to the income of Guangxi, the income is divided into five levels of CYN 5000, CYN 10,000, CYN 15,000, CYN 20,000, and CYN 25,000, and, once determined, it does not change with the number of simulation iterations.