MODELING AND EVALUATION OF SMART MINI PARKING SYSTEMS WITH PRIOR RESERVATION USING STOCHASTIC PETRI NETS

Rapid urbanization has significantly increased the demand for efficient parking solutions, particularly in city centers, making urban parking management a critical challenge. Inefficient urban parking management contributes directly to traffic congestion, increased fuel consumption, and environmental pollution. This paper evaluates the modeling and performance of a smart mini parking system that enables prior parking slot reservations through a mobile application. The system comprises seven parking spaces, allocated among four vehicle types as follows: one for handicapped vehicles, three for regular vehicles, one for small utility/cargo vehicles, and two for electric vehicles. A deterministic and stochastic Petri net model is developed to represent the dynamic reservation process, vehicle arrivals and departures, and parking durations. This approach captures the stochastic nature of vehicle flows while incorporating deterministic time constraints for fixed billing intervals. Using numerical simulations, the study evaluates the utilization rates of individual parking slots and the overall system under different vehicle arrival rates and a predefined operating profile reflecting vehicle type distribution. The simulation-based analysis highlights how arrival patterns and fleet composition affect occupancy, system saturation, and service efficiency. The findings indicate the prospective significance of smart mini parking systems, offer practical insights into optimizing parking allocation and reservation strategies in smart urban environments, and demonstrate the potential of deterministic and stochastic Petri nets as a formal tool for modeling and improving smart parking systems, thus contributing to more sustainable urban mobility solutions.