# Model for Determining Parking Demand Using Simulation-Based Pricing
## 1 Introduction  
The availability of accessible, free, or reasonably priced parking is a critical factor influencing the decision to use a private vehicle for urban travel. In line with economic and environmental objectives, parking management strategies aim to balance supply and demand, particularly when the parking system is integrated with local public transport. Parking fees act as a mechanism to influence travel mode choices [1], making parking policy an essential component of urban transport policy [2]. Parking characteristics and research methodologies are detailed in [3, 4, 5]. Parking can be classified by motivation--residential, business, commercial, public, or tourism-oriented, and by duration, as either short-term or long-term. Parking volume refers to the total number of parked vehicles over a specific period, while parking accumulation denotes the number of vehicles parked at a given moment. Additional relevant characteristics include turnover, the time spent searching for a parking space and walking distance to the destination. The utility of parking data in policymaking is discussed in [6], its role in developing parking information systems in [7], and its application in evaluating different parking strategies in [8]. Charging for parking is a key instrument in parking policy and an essential aspect of urban planning as it helps improve traffic flow, optimize land use, and support environmental conservation. Well-designed pricing strategies increase vehicle turnover and discourage car trips to city centers [9]. The conceptualization of off-street parking reform is discussed in [10]. Pricing also facilitates the achievement of desired modal splits [11]. Studies examining the impact of parking prices on travel choices, including demographic factors, trip conditions, and parking discounts, as presented in [12; 13; 14], account for demographic factors, trip conditions, and parking discounts or privileges. The effects of reduced parking supply on price increases are addressed in [15], while the influence of parking prices on street-level service and congestion reduction is explored in [16; 17]. Among immediate travel costs, parking fees exert the most significant influence on trip decisions [18]. A demand elasticity model relating to total travel cost and the impact of on-street parking on congestion is presented in [19]. The model assumes equal users who drive to their destination and either park or circle while searching. The findings support our main hypothesis (1) by confirming that raising fees can lower the overall parking demand. Variations in demand elasticity by day and time are explored in [20] using data from Dublin, revealing stronger elasticity in the morning and consistent elasticity throughout the week, except for Thursdays, which are characterized by increased shopping activity. An econometric model predicting on-street parking demand based on price elasticity is introduced in [21]. Users are willing to pay more to reduce walking distance. Data limitations due to city authorities' access policies hindered this research. The theory in [22] demonstrates the impossibility of defining a single parking price that ensures maximum garage occupancy. Over two years, 14 garages in San Francisco underwent iterative price adjustments, resulting in only acceptable price ranges. That study identified three key elements for sustainable garage operations: high occupancy, revenue generation, and the availability of free spaces. These elements are also the primary variables simulated in our study. Previous research has primarily calculated demand elasticity coefficients discrectly, often based on user surveys. Price-demand effects and predictions from stated preference surveys are discussed in [23; 24], though these methods risk discrepancies between stated and actual behavior. Therefore, researchers are encouraged to use revealed preference data, as in [25; 26; 27; 20]; however, such studies are rare due to infrequent price changes and limited data availability.