Parking Spaces Planning for Shared Vehicles Based on Visualized Data Analysis

With the continuous progress of technology and development of sharing economy, sharing vehicles have rapidly gained wide attention due to their huge market potential. The management on the shared vehicles, however, is not ripe enough to support the widely arrangement. Based on big data, this paper proposes a novel method to manage parking space of the shared vehicles based on the open available data Firstly, visualizing the GPS data of the orders and analyzing the data distribution on the road. Secondly, a density-based DBSCAN(Density-Based Spatial Clustering of Applications with Noise) clustering algorithm is employed to cluster the GPS data, determining number of parking spaces of the shared vehicles and obtaining the initial location of parking spaces. Finally, whale optimization algorithm is used to optimize the parking location and improve the utilization rate of parking spaces.