Optimizing Smart Parking Solutions in Vehicle-to-Vehicle Networks

In the era of smart cities, the demand for efficient traffic management systems has surged, particularly for smart parking solutions. This study investigates the integration of vehicle-to-vehicle communication technologies in locating available parking spaces through a practical implementation using mobile devices. We propose a novel approach employing a non-dominated multi-objective genetic optimization algorithm combined with learning automata to enhance the parking search process. The results indicate a significant 20% reduction in the time required to find parking, demonstrating the effectiveness of our algorithm in real-world scenarios. This research contributes to the advancement of intelligent transportation systems by providing a scalable solution for urban parking challenges.