Detecting Predominance of on-Street Parking Payment Schemes by Means of Linear Regression

Abstract

On street parking is one of the important and crucial components of urban traffic and transportation system. Allocation of parking space on street is major reason for traffic congestion. Optimizing traffic congestion and facilitating on street parking is a long stand issue. According to urban environment it is expected that car drivers prefers parking space based on road conditions, speed limit and surrounding activities and availability of parking space. The other major components to be ponder while searching parking space is payment method used while parking the car. This paper investigates car driver’s behaviors in selecting parking payment schemas, visualized data as well predicted via machine learning technique of linear regression analysis on the open data set of On-street Car Parking Meters with Location of City of Melbourne's in the Australian.