A Comprehensive Study of Real-Time Vacant Parking Space Detection Towards the need of a Robust Model

Abstract

Detection of vacant parking space is becoming a challenging task gradually. Space utilization and management of vehicle space is now a demandable field of research. Searching for an empty parking space in congested traffic is a time-consuming process. The existing vacant parking space detection methods are not robust or generalized for images captured from different camera viewpoints. Finding a proper parking space in a busy city is really a challenging issue and people are facing this problem on a daily basis. The main purpose of this research is to comprehensively discuss the previous researches of vacant parking space detection and compare them from different aspects. Methods used in previous researches are descriptively discussed along with their advantages and disadvantages. The frameworks of previous researches were compared on six generalized phases and the experimental results are compared in terms of dataset, accuracy, processing time and other performance measures. This research also focuses on the challenges of vision-based vacant parking space detection which will contribute to future researches and researchers can work to overcome these challenges.