Prediction of Parking Spaces and Recommendation of Parking Area in Urban Complex

Urban complex has become an essential part of our daily life. However, the management efficiency and parking experience of its parking lot have problems such as uneven utilization rate, excessive parking time and difficult parking. In order to solve these problems, we propose a novel parking management system, which improves the accuracy of short-term prediction of free parking spaces through our proposed method. And then it combines the probability distribution model to recommend the optimal parking area for drivers. In particular, based on the collected data of the parking lot in Suzhou Center and the open data of the social platform, we have established this parking management system in urban complex. The experimental results show that our parking management system not only solves the problem of drivers to blindly search for parking spaces, but also improves the management efficiency of the entire parking lot and facilitate the overall coordination of the managers.