## 2 Literature Review  
The reservation parking model, pioneered by scholars [PERSON] et al. [6], establishes a fixed-fee parking reservation system through integer linear programming. Subsequently, [PERSON] et al. [7] developed a framework for an intelligent parking reservation system via the Internet and proposed the concept of time-sharing and real-time for parking. So far, parking reservation has begun to enter the public eye. After this, an increasing number of scholars began to study the parking reservation model. [PERSON] et al. [8] controlled the inventory of the car park through reservation decision making and rationally allocated the parking spaces to achieve the goal of maximizing the profit of the car park, which was the first time that revenue management was introduced into the reservation mechanism. In order to better validate the science of reservation, [PERSON] et al. [9] verified the positive effects of reservation parking in reducing users' cruising time and controlling the flow during peak periods with an analog simulation. In addition, [PERSON] et al. [10] found that the use of reservation for parking can not only suspend traffic congestion, but also improve the utilization rate of parking spaces, thus providing full play to the time cost of the car park and improving the effectiveness of parking in addition to establishing a positive role in improving parking revenue. Further, [PERSON] and [PERSON] [11] added an appointment handling fee to the fee model to study the changes it brings. The simulation results show that the surcharge induces a further increase in the revenue of the parking lot while users spend less time searching for a parking space. [PERSON] et al. [12] extended the surcharge study by proposing a time-varying parking base fee, where the actual fee is determined through an auction to the users, which is a cumbersome process but realizes dynamic charging under the reservation mechanism, linking the user's demand to the reservation price. In this context, the research direction in the field of reserved parking is more extensive; [PERSON] et al. [13] builds a parking space allocation decision model based on the user's demand prediction results, and allocates parking spaces from a prediction point of view. [PERSON] et al. [14] analyzed from the user's psychological point of view and proposed a model for the user's choice of reservation parking. [PERSON] et al. [15] analyzed the relationship between reservation demand and price and modeled the reservation request decision with system optimality. [PERSON] et al. [16] analyzed users' behaviors and influencing factors in choosing reserved parking, shared parking, traditional car parks, and other travel modes by building a multinomial logit model, and the study showed that the parking fee, available parking spaces, and the distance of the user to reach the destination were the main factors affecting the user's travel choices. [PERSON] et al. [17] focused on the application of reserved parking, where a coil senses whether a parking space is free or not, and thus assigns a reserved parking space with a reserved parking space. As shown in Table 1, in recent years, the research directions included in the relevant research articles are indicated with \"\(\surd\)\". It can be found that basic research on reserved parking has become increasingly sophisticated, and the relationship between demand, price, and other elements has become clearer. Parking reservation research has focused on user selection, demand forecasting, space allocation, garage decision-making, and price management. Among them, the price management direction has more methods, and more mixed research from the price attributes can be divided into dynamic price, real-time price, and fixed price. Dynamic pricing is more suitable for a parking reservation mechanism from the objectives of garage revenue, user cost, and other dynamic characteristics, but there are fewer existing studies, and dynamic pricing is more complicated.