Campus Parking Planning Based on Multisource Data Analysis--Taking Mafangshan Campus of Wuhan University of Technology as an Example

Abstract

In order to solve the problems of unbalanced supply and demand of campus parking resources, chaotic parking conditions, and potential safety hazards in campus traffic, a method of campus parking system planning based on big data is proposed. Taking the Mafangshan Campus of Wuhan University of Technology as an example, from the two aspects of time dimension and spatial dimension, the paper analyzes the trend of campus parking number, vehicle’s parking time, parking density and parking space utilization rate in each area, and discards the distribution of stranded vehicles according to the vehicle collection data. Finally, according to the analysis of multi-source big data, the current situation of campus parking system is obtained, and the corresponding planning results of campus parking are obtained. Through field research and big data analysis, we can intuitively understand the distribution and utilization of the overall parking resources of the campus, and the parking planning results based on this are more practical and scientific.