Rodyti trumpą aprašą

dc.rights.licenseKūrybinių bendrijų licencija / Creative Commons licenceen_US
dc.contributor.authorČižauskas, Simonas
dc.contributor.authorUšpalytė-Vitkūnienė, Rasa
dc.date.accessioned2026-04-24T11:06:42Z
dc.date.available2026-04-24T11:06:42Z
dc.date.issued2026
dc.date.submitted2026-02-18
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/160375
dc.description.abstractPublic transport is like a living organism that is constantly changing along with the city and the needs of its residents. Based on the changes in the city, its infrastructure or the habits of its residents, the public transport system must also change. One of the main tools for understanding the public transport in urban areas is passenger origin-destination (OD) matrices. OD matrices are compiled based on mass population surveys, during which the city is divided into zones, and the collected data is used to create travel patterns. Such studies implementation is expensive and repeated infrequently – usually every few or even ten years. Currently, on-board computers collect a significant amount of data about daily citizens’ trips, but the main problem is that this data is not enough to create an O-D matrix, because only boarding data is recorded. The second largest city in Lithuania was chosen for the study due to the abundance of data collected. The aim of this study is to develop a methodology based only on boarding data, allowing to reflect the passenger origin-destination matrix. Two methods were later tested during the study: the first, matching sequential entries based on that the same anonymised card identifier, and the second, the time that the passenger gets off at the stop where they get back on. The results of these methods are analyzed and evaluated at the stop and zone level.en_US
dc.format.extent8 p.en_US
dc.format.mediumTekstas / Texten_US
dc.language.isoenen_US
dc.relation.urihttps://etalpykla.vilniustech.lt/handle/123456789/160340en_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectpublic transporten_US
dc.subjectorigin-destination matrixen_US
dc.subjectpassengers’ habitsen_US
dc.subjectpublic transport modellingen_US
dc.titleMethods of determining the O-D matrix in the absence of data surveysen_US
dc.typeKonferencijos publikacija / Conference paperen_US
dcterms.accessRightsLaisvai prieinamas / Openly availableen_US
dcterms.accrualMethodRankinis pateikimas / Manual submissionen_US
dcterms.alternativeRoads, railways and smart citiesen_US
dcterms.dateAccepted2026-02-22
dcterms.issued2026-04-24
dcterms.licenseCC BYen_US
dcterms.references12en_US
dc.description.versionTaip / Yesen_US
dc.contributor.institutionUAB “Kauno autobusai”en_US
dc.contributor.institutionVilniaus Gedimino technikos universitetasen_US
dc.contributor.institutionVilnius Gediminas Technical Universityen_US
dc.contributor.facultyAplinkos inžinerijos fakultetas / Faculty of Environmental Engineeringen_US
dc.contributor.departmentKelių katedra / Department of Roadsen_US
dcterms.sourcetitle13th International Conference “Environmental Engineering” (ICEE-2026)en_US
dc.identifier.eisbn9786094764448en_US
dc.identifier.eissn2029-7092en_US
dc.publisher.nameVilnius Gediminas Technical Universityen_US
dc.publisher.nameVilniaus Gedimino technikos universitetasen_US
dc.publisher.countryLithuaniaen_US
dc.publisher.countryLietuvaen_US
dc.publisher.cityVilniusen_US
dc.identifier.doihttps://doi.org/10.3846/enviro.2026.2313en_US


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Rodyti trumpą aprašą

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