A cloud architecture to integrate a multi-agent smart parking system

Abstract

Smart parking systems are becoming a solution to recurring issues as the number of vehicles in traffic rises in major cities, which can be related to vehicle traffic congestion, unnecessary time spent searching for parking spots, and, consequently, environmental issues. The purpose of these systems is to help drivers who are searching for available parking spaces or who want to reserve for a specified period of time, quickly and, if possible, near the desired location. In this context, there are several modules within smart parking systems that may include cyber-physical systems, multi-agent systems, dynamic pricing and artificial intelligence. This dissertation presents the development of a smart parking system architecture, using Cloud-based technology to integrate a multiagent system into a scalable, decentralized, adaptable and safe environment. The proposed architecture was tested using, as a case study, a web system developed for the management and analysis of smart parking lots, as well as an application for mobile devices, which allows users to interact with multiple functionalities available in this system. Results obtained demonstrate that the implementation of the proposed architecture offers an efficient communication between users who use parking resources and the multi-agent system responsible for the autonomy and intelligence of the parking system.