Efficient management of parking spaces is a critical aspect of urban mobility in large cities, particularly in Bulgaria where rapid urbanization poses significant challenges. In this paper, we propose a novel approach utilizing intuitionistic fuzzy estimates within the framework of a smart city intelligent transport system (ITS) to optimize the utilization of parking spaces. Leveraging real-time data from sensors and IoT devices, our system employs intuitionistic fuzzy logic to model the uncertainty and imprecision inherent in parking demand prediction. By integrating multiple sources of information, including historical usage patterns, traffic flow data, and external factors such as events and holidays, our approach enables more accurate estimation of parking space availability. Furthermore, the intuitive nature of intuitionistic fuzzy estimates enhances the interpretability of the system, facilitating decision-making for urban planners and transportation authorities. Our research contributes to the advancement of smart city initiatives by offering a practical solution for optimizing parking management in large urban centers, thereby promoting sustainable and efficient urban mobility.