## 1 Introduction  
With the development of intelligent transportation, advanced traveler information systems can provide bus passengers with real-time traffic information, allowing them to make reasonable travel plans. Providing this information to bus passengers will affect their travel time and route choice, thereby improving their travel efficiency. However, whether bus passengers will accept this induced information ultimately depends on their route selection behavior. Therefore, the travel route selection behavior of bus passengers under the information-induced condition has attracted the attention of many researchers. [PERSON] et al. [1] assembled data on ridership and stop amenities, including Real-Time Information System (RTIS), shelters, lighting, litter receptacles, benches, and bike hoops. Additionally, the impact of bus stop facilities on transit ridership through the above data was analyzed. Study results have shown that RTIS have a significant impact on transit ridership. From the perspective of travelers, [PERSON] et al. [2] analyzed the characteristics of passengers' bus choice behavior under RTI based on revealed-preference and stated-preference survey data. [PERSON] et al. [3] refined intelligent bus information into bus route information, estimated arrival time information, in-vehicle congestion information, total travel information, and fare information; the researchers then analyzed the impact of the above information on passenger travel paths. These studies have shown that bus itinerary information and in-vehicle congestion information have a significant impact on passengers' travel route choices. [PERSON] et al. [4] analyzed the impact of bus congestion information on passengers' bus-route selection and obtained the characteristics of passengers' bus selection behavior under different congestion levels. From this, they proposed a route selection model that considers bus congestion information. [PERSON] et al. [5] improved an existing bus control strategy by providing passengers with real-time bus congestion information (RTCI) to reduce the aggregation effect of bus passengers. [PERSON] et al. [6] discussed the bus-route selection behavior of passengers when they saw two buses arriving at their destination and knew the real-time congestion information of the bus in advance. The authors then established a related model based on the obtained data to improve the bus route schedule. The above studies show that real-time bus information has a significant impact on passengers' travel behavior. Moreover, they demonstrated that this information can be used to establish corresponding route-selection or bus-scheduling models based on the behavioral characteristics of passengers to improve the travel efficiency of passengers. Solutions from the realm of game theory have been proposed for various transportation topics, such as traffic signal control [7], lane-changing behavior in a connected environment [8], and the nature of equilibrium [9] to name a few. In terms of traffic choice behavior, [PERSON] et al. [10] established a traveler's traffic choice behavior model using evolutionary game theory based on the assumption that travelers have incomplete road network information and bounded rationality of choice behavior. This study theoretically proved the applicability of evolutionary game theory in the analysis of traffic choice behavior. [PERSON] [11] quantified the trade-off between the minimization of train delays and passenger travel times and the performance, stability, and convergence of the equilibrium point based on game theory. The proposed game theoretical approach is able to easily consider information and interdependence of the actions of multiple stakeholders. Through relevant experiments and game theory, [PERSON] [12] studied the interaction of route choices among passengers and their final decision-making behavior under the condition that travelers obtain public transportation congestion information.