Mobile outdoor parking space detection application

Abstract

Finding a vacant parking space in outdoor parking lots is a daily concern of most vehicle drivers during rush hours, especially in the urban context. In this paper, an outdoor parking space vacancy detection system is proposed, using mobile devices to improve parking space searching experience for vehicle drivers by providing them with the location and occupancy information of parking spaces. The system uses state-of-the-art image recognition algorithm, namely Convolutional Neural Network with a Raspberry Pi to identify vacant parking spaces from a parking lot image retrieved in real time via an IP camera. A university parking lot has been chosen as the test bed to deploy the proposed system for real time parking space vacancy detection. An Android smartphone application called Driver App is developed to enable ubiquitous visualization of real time outdoor parking spaces occupancy information for vehicle drivers. Evaluation outcomes based on the responses to System Usability Scale (SUS) questionnaire revealed high usability of the Driver App as a tool that provides smart parking service to assist vehicle drivers in searching for a vacant parking space.