## 3 Methodology
For the travel distance attribute, considering that the individual travel distance varies from time to time, based on the analysis of the average travel distance metric derived from one month of freeway toll collection data in Guangxi, in which the largest travel distance is 500 km, a random number within 500 km is defined as the maximum travel distance of the individual, and the travel distance in each simulation iteration is a uniformly distributed random number within the range of the maximum travel distance. The initial route preference attribute is a uniformly distributed random number between 0 and 1, which represents the probability of individuals choosing to travel via the freeway or parallel national/provincial roads, with the larger values indicating that individuals tend to use freeways for travel. The initial path preference attribute does not change with the number of simulation iterations. Then, depending on the simulation demand in each round, the degree of rationality of the agents, the speed of the freeway, and the speed of the national and provincial arterial roads are set by the control. In this study, the degree of rationality is set in the interval of 0-1, with 0 indicating that individuals are completely irrational, and the travel route selection only considers the route preference; and 1 indicating that individuals are completely rational, and the travel route selection only considers the travel cost. The freeway speed has been set between 70 km/h and 120 km/h and the parallel road speed has been set between 50 and 80 km/h. The most critical part is to execute the route selection behavior of the agent to determine whether it chooses to take the freeway or the parallel road. The route selection behavior is divided into two parts, with the first based on the distance of each trip of the agents, where we estimate the cost required to take the freeway or the parallel road, respectively. The cost formulas for the two routes are shown in Equations (1) and (2). \[C_{F}=Dis\times Rate+\frac{Dis}{V_{F}}\times\frac{\gamma Inc}{21\times 8} \tag{1}\]\[C_{p}=\frac{Dis}{V_{P}}\times\frac{\gamma Inc}{21\times 8} \tag{2}\]  
where \(C_{F}\) and \(V_{F}\) denote the cost and speed of the freeway and \(C_{p}\) and \(V_{p}\) denote the cost and speed of the parallel road. _Rate_ represents the toll rate of the freeway, which we set between CYN 0 and 1 per kilometer. _Dis_ is the travel distance and _Inc_ refers to the monthly income. \(\gamma\) is the modifying factor, as the time spent on the journey might be more \"expensive\" than the average value denoted by \(\frac{Inc}{21\times 8}\), that is, the ratio of monthly income to monthly working hours. After computing the travel costs of the two roads, the route with the lower travel cost is viewed as the rationally chosen road (\(RR\)), which is 1 if the lower-cost road is a freeway and 0 if the lower-cost road is a parallel road. Then, we find the following:  
\[R=Rationality\times RR+(1-Rationality)\times RP \tag{3}\]  
where _Rationality_ is the degree of rationality, \(RP\) is the road chosen in preference, and the value equals the route preference. The routes chosen for the two scenarios may or may not match each other. An individual with a degree of rationality of 1 has a route choice outcome in the formula that depends entirely on \(RR\). Whereas an individual with a degree of rationality of 0 has a route choice outcome in the formula that depends entirely on \(RP\), i.e., route preference (\(P\)). Thus, when the variable \(R\) has a value of less than 0.5, the route selection turns out to be a parallel road, and, when the value of \(R\) is greater than 0.5, the route selection turns out to be a freeway. The final step is to update the individual's route preferences, as the outcomes that result from each actual behavior enhance or attenuate this preference. To achieve the goal, we define the reward (\(Rew_{t}\)) for agents at the current moment \(t\).