Survey of Smart Parking Systems
dc.contributor.author
dc.date.accessioned
2020-06-09T07:18:09Z
dc.date.available
2020-06-09T07:18:09Z
dc.date.issued
2020-06-02
dc.identifier.uri
dc.description.abstract
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
dc.description.sponsorship
This work was funded by the DURSI consolidated research group Smart IT Engineering and Services
(SITES) (ref. 2017 SGR‐1551), Institute of Informatics and Applications at the University of Girona, and by a PhD
scholarship (M.D.) by the National Council for Scientific and Technical Research (CONICET), Argentina
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
MDPI (Multidisciplinary Digital Publishing Institute)
dc.relation.isformatof
Reproducció digital del document publicat a: https://doi.org/10.3390/app10113872
dc.relation.ispartof
Applied Sciences, 2020, vol. 10, núm. 11, p. 3872
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Articles publicats (D-ATC)
dc.rights
Attribution 4.0 International
dc.rights.uri
dc.subject
dc.title
Survey of Smart Parking Systems
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.type.peerreviewed
peer-reviewed
dc.identifier.eissn
2076-3417