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dc.contributor.authorZapolskytė, Simona
dc.contributor.authorBurinskienė, Marija
dc.contributor.authorTrepanier, Martin
dc.date.accessioned2023-09-18T20:33:42Z
dc.date.available2023-09-18T20:33:42Z
dc.date.issued2020
dc.identifier.issn1822-427X
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/150733
dc.description.abstractWhile many cities around the world qualify themselves as “smart cities”, there is no comprehensive way to evaluate to what extent they are “smart”. This article proposes a framework for comparison of the level of “smartness” of the urban mobility systems. The most relevant indicators that have the greatest impact on smart mobility systems were selected in the course of literature review. The impact of indicators on smart mobility systems is variable. Evaluating smart mobility systems, different authors distinguish between different indicators, which usually do not duplicate. The paper categorizes the indicators of the smart mobility system into five groups, called “factors”: motor travel and congestion reduction measures; pollution reduction measures; travel safety and accident reduction measures; traffic management tools and services; smart infrastructure measures. A number of indicators are attributed to each of the listed groups. A Multiple Criteria Decision-Making method, namely, the Analytic Hierarchy Process (AHP) method, has been used to evaluate the significance of the smartness level used in the research. This method bases the weighting of subjective criteria on expert judgement. Rank correlation is used to determine the consistency of expert opinions. A model has been developed to compare smart mobility systems of individual cities and their infrastructure.eng
dc.formatPDF
dc.format.extentp. 196-224
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyINSPEC
dc.relation.isreferencedbyTOC Premier
dc.relation.isreferencedbyVINITI
dc.relation.isreferencedbyTRIS Online
dc.relation.isreferencedbyCurrent Abstracts (EBSCO)
dc.relation.isreferencedbyDOAJ
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://bjrbe-journals.rtu.lv/article/view/bjrbe.2020-15.501
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:70317277/datastreams/MAIN/content
dc.titleEvaluation criteria of smart city mobility system using MCDM method
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references38
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionPolytechnique Montréal, Interuniversitary Research Centre on Enterprise Networks, Logistic and Transportation (CIRRELT), Montréal, Canada
dc.contributor.facultyAplinkos inžinerijos fakultetas / Faculty of Environmental Engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.researchfieldT 003 - Transporto inžinerija / Transport engineering
dc.subject.vgtuprioritizedfieldsTD05 - Miesto judumas / Urban mobility
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enbenchmarking
dc.subject.enintelligent infrastructure
dc.subject.enmulticriteria analysis
dc.subject.ensmart city mobility system
dc.subject.ensmartness index
dcterms.sourcetitleThe Baltic journal of road and bridge engineering
dc.description.issueiss. 4
dc.description.volumevol. 15
dc.publisher.nameRiga Technical University
dc.publisher.cityRiga
dc.identifier.doi000576251900010
dc.identifier.doi10.7250/bjrbe.2020-15.501
dc.identifier.elaba70317277


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