ASPIRE: An Agent-Oriented Smart Parking Recommendation System for Smart Cities

Abstract

An Agent-oriented Smart Parking Recommendation System for Smart Cities (ASPIRE) using Internet of Things (IoT) is proposed in which significant consideration is given to the driver's parking preferences such as type of parking sought, the maximum price that the parker is willing to pay, and the maximum time to walk from parking space to the destination that the parker can tolerate. ASPIRE is a lightweight, scalable, and adaptable system that automates the workflow of reserving the best parking spots. It employs a novel parking broker-a software agent that leverages valuable route planning information from other traffic information services, and promotes road-safety by minimizing the need for parkers to interact with their smartphones or onboard units, thus lowering distracted driving. The main contribution of this paper is the novel adoption of lightweight Analytic Hierarchy Process (AHP) in order to determine the best parking space. In addition, the parking record collected by ASPIRE can provide local governments with statistics for building future parking lots. ASPIRE's parking network and architecture, system workflow, strategy model, and simulation highlight the importance of the desirable feature such as satellite navigation, indoor navigation, event data recording, parking reference, traffic and weather information, and parking reservations.