Towards Sustainable Parking: Analyzing the Characteristics of Periodic Off-Street Parking Lots and Their Application in Shared Parking

The pollution and congestion caused by the shortage of parking spaces are threatening the sustainable development of cities. Smart parking platforms are one of the major tools to solve the problem by providing the efficient usage of parking resources. However, current platforms can only realize limited functions, and shared parking is far from being implemented on a large scale. Since off-street parking provides the majority of potential shared parking spaces, this paper takes periodic off-street parking lots as the starting point for opening the shared parking market. Based on data from the Ningbo Yongcheng parking platform, power spectral density (PSD) and the autocorrelation function (ACF) are used to identify periodic parking lots. A Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based method is applied to clustering the occupancy time series. Land use, user type, parking duration, and parking patterns are then analyzed to study shared parking supply characteristics. The results show that (1) 31.3% of off-street parking lots are periodic parking lots, and 90.3% of them have regular users exceeding 50%. (2) Periodic parking lots are classified into four types. Most parking lots show convex flat peak, double peak, or triple peak characteristics. (3) The shared parking spaces demonstrate spatial and temporal imbalances. But in a small area, even considering the concentration of land use and the peak period, there are still enough spaces available. The above research is of significance for the large-scale implementation of shared parking, which can promote the sustainable development of a city.