Hybrid Framework for Parking Slot Allocation Using Double Auction and Cooperative Game Theory in Fog-Based Systems

The rapid growth of urban transportation necessitates innovative strategies for efficient parking management. Fog-based smart parking systems help reduce latency and improve resource use, but challenges remain in achieving fair and optimal slot allocation. This study presents a hybrid framework that combines a multi-attribute-based double auction mechanism with cooperative game theory. The double auction allocates parking slots fairly, considering both economic and non-price factors like proximity and reputation, while cooperative game theory fosters user coalitions to boost efficiency and satisfaction. By utilizing fog nodes for real-time processing, the system minimizes cloud reliance, ensuring low latency and scalability. Simulations demonstrate significant gains in efficiency, fairness, and responsiveness, showcasing the framework’s potential to enhance resource use and promote collaboration for smarter urban mobility.