Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/9493
DC FieldValueLanguage
dc.contributor.authorAntoniou, Constantinos-
dc.contributor.authorGikas, Vassilis-
dc.contributor.authorPapathanasopoulou, Vasileia-
dc.contributor.authorDanezis, Chris-
dc.contributor.authorPanagopoulos, Athanasios D.-
dc.contributor.authorMarkou, Ioulia-
dc.contributor.authorEfthymiou, Dimitrios-
dc.contributor.authorYannis, George D.-
dc.contributor.authorPerakis, Harris-
dc.date.accessioned2017-02-06T10:50:55Z-
dc.date.available2017-02-06T10:50:55Z-
dc.date.issued2015-01-01-
dc.identifier.citationTransportation Research Record, 2015, vol. 2489, no. 1, Pages 66-76.en_US
dc.identifier.issn03611981-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/9493-
dc.description.abstractGlobal navigation satellite systems have tremendous impact and potential in the development of intelligent transportation systems and mobility services and are expected to deliver significant benefits, including increased capacity, improved safety, and decreased pollution. However, there are situations in which there might not be direct location information about vehicles, for example, in tunnels and in indoor facilities such as parking garages and commercial vehicle depots. Various technologies can be used for vehicle localization in these cases, and other sensors that are currently available in most modern smartphones, such as accelerometers and gyroscopes, can be used to obtain information directly about the driving patterns of individual drivers. The objective of this research is to present a framework for vehicle localization and modeling of driving behavior in indoor facilities or, more generally, facilities in which global navigation satellite system information is not available. Localization technologies and needs are surveyed and the adopted methodology is described. The case studies, which use data from multiple types of sensors (including accelerometers and gyroscopes from two smartphone platforms as well as two reference platforms), provide evidence that the opportunistic smartphone sensors can be useful in identifying obstacles (e.g., speed humps) and maneuvers (e.g., U-turns and sharp turns). These data, when crossreferenced with a digital map of the facility, can be useful in positioning the vehicles in indoor environments. At a more macroscopic level, a methodology is presented and applied to determine the optimal number of clusters for the drivers' behavior with a mix of suitable indexes.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofTransportation Research Record: Journal of the Transportation Research Boarden_US
dc.rights© National Academy of Sciences.en_US
dc.subjectGlobal navigationen_US
dc.subjectSatellite systemsen_US
dc.subjectSmartphonesen_US
dc.subjectTransportationen_US
dc.titleLocalization and driving behavior classification with smartphone sensors in direct absence of global navigation satellite systemsen_US
dc.typeArticleen_US
dc.doi10.3141/2489-08en_US
dc.collaborationTechnische Universität Münchenen_US
dc.collaborationNational Technical University Of Athensen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryCivil Engineeringen_US
dc.journalsOpen Accessen_US
dc.countryGermanyen_US
dc.countryGreeceen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.3141/2489-08en_US
dc.relation.issue1en_US
dc.relation.volume2489en_US
cut.common.academicyear2014-2015en_US
dc.identifier.spage66en_US
dc.identifier.epage76en_US
item.grantfulltextopen-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.fulltextWith Fulltext-
crisitem.journal.journalissn2169-4052-
crisitem.journal.publisherSage-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-0248-1085-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Άρθρα/Articles
Files in This Item:
File Description SizeFormat
Danezis.pdf4.99 MBAdobe PDFView/Open
CORE Recommender
Show simple item record

SCOPUSTM   
Citations

8
checked on Nov 9, 2023

WEB OF SCIENCETM
Citations

7
Last Week
0
Last month
0
checked on Oct 29, 2023

Page view(s) 50

418
Last Week
0
Last month
0
checked on Nov 8, 2024

Download(s)

349
checked on Nov 8, 2024

Google ScholarTM

Check

Altmetric


Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.