The Adaptive Recommendation Mechanism for Distributed Parking Service in Smart City

Recently, there are many researchers investigate about the recommendation system for improving the parking experience. In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RE module will transmit the vehicle location information and parking space requirement to parking congestion cloud center (PCCC) when the drivers need to find a parking space. Moreover we use cellular automata model mechanism for those parking spaces in the parking lot, it can adjust the situation that some parking lots are full and some are not. We also adopted the Artificial Fish Swarm Algorithm to build this two parts parking recommendation mechanism. Here the PCCC can compute with vehicle location information, nearest parking lot, parking lot status and the same or opposite driving direction. We take the driving direction into consideration can reduce road congestion and speed up finding a parking space from vehicles turning around. The current study evaluates the performance of the approach by conducting computer simulations. Simulation results the strengths of the proposed smart parking mechanism in terms of increased congestion avoiding and decrease parking space finding time.