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...
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| Published in: | Applied sciences Vol. 10; no. 11; p. 3872 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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MDPI AG
01.06.2020
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| ISSN: | 2076-3417, 2076-3417 |
| Online Access: | Get full text |
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| 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. |
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| AbstractList | 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. Keywords: smart parking systems; survey; vehicle routing problem; vehicle detection techniques; routing algorithms 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. |
| Audience | Academic |
| Author | Aciar, Silvana Fabregat, Ramon Diaz Ogás, Mathias Gabriel |
| Author_xml | – sequence: 1 givenname: Mathias Gabriel orcidid: 0000-0003-3562-537X surname: Diaz Ogás fullname: Diaz Ogás, Mathias Gabriel – sequence: 2 givenname: Ramon orcidid: 0000-0002-3551-7304 surname: Fabregat fullname: Fabregat, Ramon – sequence: 3 givenname: Silvana surname: Aciar fullname: Aciar, Silvana |
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| CitedBy_id | crossref_primary_10_1080_23249935_2024_2409229 crossref_primary_10_1007_s10796_023_10453_y crossref_primary_10_1007_s13177_024_00420_5 crossref_primary_10_3390_su13084211 crossref_primary_10_3390_app11188680 crossref_primary_10_3390_electronics13203997 crossref_primary_10_3390_s21113783 crossref_primary_10_3390_network2020015 crossref_primary_10_3390_futuretransp5030110 crossref_primary_10_1080_17445760_2023_2246166 crossref_primary_10_1007_s12239_023_0025_6 crossref_primary_10_1109_JSEN_2023_3345037 crossref_primary_10_1007_s12243_021_00878_4 crossref_primary_10_1109_ACCESS_2025_3577489 crossref_primary_10_3390_su16020856 crossref_primary_10_1007_s13042_023_02056_5 crossref_primary_10_3390_s24041288 crossref_primary_10_1109_ACCESS_2023_3327306 crossref_primary_10_1109_TITS_2023_3279024 crossref_primary_10_3390_su151713174 crossref_primary_10_1007_s13278_022_00981_x crossref_primary_10_3390_electronics10243184 crossref_primary_10_1109_TITS_2021_3133713 crossref_primary_10_1109_ACCESS_2024_3484758 crossref_primary_10_3233_IDT_230339 crossref_primary_10_1016_j_measen_2022_100524 crossref_primary_10_1016_j_eswa_2022_116731 crossref_primary_10_1007_s11042_022_13958_x crossref_primary_10_1109_TSC_2023_3286332 crossref_primary_10_3390_s24072036 crossref_primary_10_3390_smartcities5040078 crossref_primary_10_1051_e3sconf_202456503024 crossref_primary_10_1007_s11831_025_10250_7 |
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