Survey of smart parking systems

The large number of vehicles constantly seeking access to congested areas in cities means that finding a public parking place is often difficult and causes problems for drivers and citizens alike. In this context, strategies that guide vehicles from one point to another, looking for the most optimal path, are needed. Most contributions in the literature are routing strategies that take into account different criteria to select the optimal route required to find a parking space. This paper aims to identify the types of smart parking systems (SPS) that are available today, as well as investigate the kinds of vehicle detection techniques (VDT) they have and the algorithms or other methods they employ, in order to analyze where the development of these systems is at today. To do this, a survey of 274 publications from January 2012 to December 2019 was conducted. The survey considered four principal features: SPS types reported in the literature, the kinds of VDT used in these SPS, the algorithms or methods they implement, and the stage of development at which they are. Based on a search and extraction of results methodology, this work was able to effectively obtain the current state of the research area. In addition, the exhaustive study of the studies analyzed allowed for a discussion to be established concerning the main difficulties, as well as the gaps and open problems detected for the SPS. The results shown in this study may provide a base for future research on the subject.Fil: Diaz Ogás, Mathias Gabriel. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Fabregat Gesa, Ramon. Universidad de Girona; EspañaFil: Aciar, Silvana Vanesa. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentin

Predicting Demand for Smart Parking Systems

Kiire areng infotehnoloogias on võimaldanud inimestel, kes ei ole antud ala eksperdid, luua täpseid masinõppe mudeleid, mis suudavad õppida olemasolevatest andmetest. Selliste mudelite rakendamine linnaplaneerimisel esinevatele probleemidele võib aidata luua paremaid elamistingimusi suurlinnades. Antud töö keskendub tehisnärvivõrgule, mis suudaks ennustada parkimisala hõivatust. Töö käigus välja töötatud mudeli integreerimine süsteemi, mis suunab inimesi parkimiskohtadele võiks anda väärtusliku toote, mis vähendaks liiklusummikuid ja parkimiskoha otsimiseks kuluvat aega.The rapid development of information technologies has enabled to create accurate machine learning models that could learn from the existing data without the need of an expert in the field. Applying these models in the field of urban design problems could help to create better living conditions in large cities. This research focuses on creating a neural network that could predict parking area occupancy. Integrating the model to a parking guidance platform would produce a valuable product that could help to reduce the traffic congestions and the cruising time for a parking spot

Smart parking systems by using Espresso Lite 2.0

There are more and more vehicles on the road in every country, which have to be parked in spaces that are becoming increasingly packed. This is a big challenge especially for city planners, architects, and building owners. To meet this demand, the innovative and space saving-parking system is created. This is the new way of technology that can be applied to all users and it is more efficient than the previous parking systems. All buildings including hospitals, government building, shopping complex can access and apply this technology. This paper proposed a program that combined with the iOS system and connected through wireless connection. In addition, it will be connected to the mobile phones using this technology. Before the data can be displayed, the mobile phone has to be installed with BLINK's application that can be downloaded from the apple store. After this application is installed, then apps will show the available parking slot in the specific parking area. Any parking spaces can be assessed anywhere and anytime as long as users have internet connection to their smartphones. This paper proposed to develop the iOS apps that can show and update the parking spaces that are available and the hardware is designed by using ESPresso Lite 2.0 board

Smart Parking Systems Design and Integration Into IoT

This paper looks at two smart parking reservation algorithms, and examines the ongoing efforts to connect smart systems of different domains in a city\u27s infrastructure. The reservation algorithms are designed to improve the performance of smart parking systems. The first algorithm considers the distance between parking areas and the number of free parking spaces in determining a parking space. The second algorithm uses distance between parking areas and driver destination, parking price, and the number of unoccupied spaces for each parking area. Neither of these smart parking systems cover how they could fit into a larger scale smart system. As a result, we also look at how interconnection of smart systems is a big priority in the European Union. The researchers there aim to avoid vertical silos of information. Sharing smart system information between different domains can be used to create new or improved services

Development of a Middleware between SUMO simulation tool and JaCaMo framework

Smart City has an infrastructure that works with technology to reduce daily problems. The lack of parking spots is one of these problems that can be controlled by creating Smart Parking systems. The MAPS (Multi-Agent Parking System) project studies and develops multi-agent systems for smart parking using JaCaMo framework to implement agents and artifacts. This paper presents the so-called MAPS-SUMO, a middleware between the MAPS project and SUMO, a simulation tool used for urban traffic. Our middleware allows a graphical representation for the simulation executed by MAPS agents

Improved utilization for “smart parking systems” based on paging technique

Considering the rapid urbanization and the road congestion, the development of smart parking solutions becomes more crucial, especially in terms of economic interests. Thanks to IoT-connectivity and the cloud-integrated platforms, drivers can easily find a vacant parking lot with smart parking services. This paper intervenes in the profit of parking management systems. The paper proposes a new technique “paging technique” which increases the utilization factor of parking slots. The proposed method takes advantage of the idle time that exists between two successful parking services in the same slot. Besides, it investigates the possibility of using the idle times from different parking slots to provide a continuous parking time for an additional car. The paging technique is optimally implemented using mixed-integer linear programming that maximizes the utilization factor for the parking slots with minimum car transitions. Moreover, a data model for the parking management system has been constructed while considering the three major customers, namely, regular, prepaid, and walk-in customers. The difference between fixed and dynamic pricing for parking has been investigated. The technique has been validated using GAMS optimization software and hardware using DSP with Coin-or branch and cut solver (CBC) under real-life conditions. The statistical results prove that the revenue for the proposed parking system has increased significantly. Finally, a comparative analysis is performed, benchmarking our proposed method against recent competing algorithms in real world applications to demonstrate its superiority