Travel time estimation in public transportation using bus location data
Resumen:
The user experience of passengers using public transportation is highly sensitive to travel time. In this regard, travel time is a key input to assess the quality of service o ered by a public transportation system and to compute performance and service-level metrics. Moreover, travel time is needed to evaluate the accessibility to di erent opportunities in the city (e.g., employment, commercial activities, education) that can be reached using public transportation. This article presents a data analysis approach to estimate in-vehicle travel time in public transportation systems. Vehicle location data, bus stops locations, bus lines routes, and timetables from the public transportation system in Montevideo, Uruguay, are considered in the case study used to evaluate the proposed approach. Results are compared against scheduled timetables and are used to compute several performance indicators of the public transportation system of the city.
| 2022 | |
| Proyecto ANII. FSDA_1_2018_1_154502 - Accesibilidad territorial, universal y sostenible: caracterización del sistema de transporte intermodal de Montevideo | |
|
Travel time public transportation Data analysis GPS data |
|
| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/31504 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| _version_ | 1807522889670328320 |
|---|---|
| author | Massobrio, Renzo |
| author2 | Nesmachnow, Sergio |
| author2_role | author |
| author_facet | Massobrio, Renzo Nesmachnow, Sergio |
| author_role | author |
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| collection | COLIBRI |
| dc.contributor.filiacion.none.fl_str_mv | Massobrio Renzo, Universidad de la República (Uruguay). Facultad de Ingeniería. Nesmachnow Sergio, Universidad de la República (Uruguay). Facultad de Ingeniería. |
| dc.creator.none.fl_str_mv | Massobrio, Renzo Nesmachnow, Sergio |
| dc.date.accessioned.none.fl_str_mv | 2022-05-06T17:30:43Z |
| dc.date.available.none.fl_str_mv | 2022-05-06T17:30:43Z |
| dc.date.issued.none.fl_str_mv | 2022 |
| dc.description.abstract.none.fl_txt_mv | The user experience of passengers using public transportation is highly sensitive to travel time. In this regard, travel time is a key input to assess the quality of service o ered by a public transportation system and to compute performance and service-level metrics. Moreover, travel time is needed to evaluate the accessibility to di erent opportunities in the city (e.g., employment, commercial activities, education) that can be reached using public transportation. This article presents a data analysis approach to estimate in-vehicle travel time in public transportation systems. Vehicle location data, bus stops locations, bus lines routes, and timetables from the public transportation system in Montevideo, Uruguay, are considered in the case study used to evaluate the proposed approach. Results are compared against scheduled timetables and are used to compute several performance indicators of the public transportation system of the city. |
| dc.description.es.fl_txt_mv | Publicado en Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555. Springer, Cham. |
| dc.description.sponsorship.none.fl_txt_mv | Proyecto ANII. FSDA_1_2018_1_154502 - Accesibilidad territorial, universal y sostenible: caracterización del sistema de transporte intermodal de Montevideo |
| dc.format.extent.es.fl_str_mv | 15 p. |
| dc.format.mimetype.es.fl_str_mv | application/pdf |
| dc.identifier.citation.es.fl_str_mv | Massobrio, R y Nesmachnow, S. Travel time estimation in public transportation using bus location data [Preprint] Publicado en: Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555, 2022. Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-96753-6_14. |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/31504 |
| dc.language.iso.none.fl_str_mv | en eng |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.es.fl_str_mv | Travel time public transportation Data analysis GPS data |
| dc.title.none.fl_str_mv | Travel time estimation in public transportation using bus location data |
| dc.type.es.fl_str_mv | Preprint |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/preprint |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/submittedVersion |
| description | Publicado en Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555. Springer, Cham. |
| eu_rights_str_mv | openAccess |
| format | preprint |
| id | COLIBRI_40704cbb3c0e7c844a7116317f4cf411 |
| identifier_str_mv | Massobrio, R y Nesmachnow, S. Travel time estimation in public transportation using bus location data [Preprint] Publicado en: Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555, 2022. Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-96753-6_14. |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/31504 |
| publishDate | 2022 |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | mabel.seroubian@seciu.edu.uy |
| repository.name.fl_str_mv | COLIBRI - Universidad de la República |
| repository_id_str | 4771 |
| rights_invalid_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| spelling | Massobrio Renzo, Universidad de la República (Uruguay). Facultad de Ingeniería.Nesmachnow Sergio, Universidad de la República (Uruguay). Facultad de Ingeniería.2022-05-06T17:30:43Z2022-05-06T17:30:43Z2022Massobrio, R y Nesmachnow, S. Travel time estimation in public transportation using bus location data [Preprint] Publicado en: Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555, 2022. Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-96753-6_14.https://hdl.handle.net/20.500.12008/31504Publicado en Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555. Springer, Cham.The user experience of passengers using public transportation is highly sensitive to travel time. In this regard, travel time is a key input to assess the quality of service o ered by a public transportation system and to compute performance and service-level metrics. Moreover, travel time is needed to evaluate the accessibility to di erent opportunities in the city (e.g., employment, commercial activities, education) that can be reached using public transportation. This article presents a data analysis approach to estimate in-vehicle travel time in public transportation systems. Vehicle location data, bus stops locations, bus lines routes, and timetables from the public transportation system in Montevideo, Uruguay, are considered in the case study used to evaluate the proposed approach. Results are compared against scheduled timetables and are used to compute several performance indicators of the public transportation system of the city.Submitted by Machado Jimena (jmachado@fing.edu.uy) on 2022-05-06T17:02:18Z No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) MN22.pdf: 720341 bytes, checksum: 0b46c75d8d385b7df464cd9e89dc3719 (MD5)Approved for entry into archive by Machado Jimena (jmachado@fing.edu.uy) on 2022-05-06T17:11:17Z (GMT) No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) MN22.pdf: 720341 bytes, checksum: 0b46c75d8d385b7df464cd9e89dc3719 (MD5)Made available in DSpace by Luna Fabiana (fabiana.luna@seciu.edu.uy) on 2022-05-06T17:30:43Z (GMT). No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) MN22.pdf: 720341 bytes, checksum: 0b46c75d8d385b7df464cd9e89dc3719 (MD5) Previous issue date: 2022Proyecto ANII. FSDA_1_2018_1_154502 - Accesibilidad territorial, universal y sostenible: caracterización del sistema de transporte intermodal de Montevideo15 p.application/pdfenengLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)Travel timepublic transportationData analysisGPS dataTravel time estimation in public transportation using bus location dataPreprintinfo:eu-repo/semantics/preprintinfo:eu-repo/semantics/submittedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaMassobrio, RenzoNesmachnow, SergioLICENSElicense.txtlicense.txttext/plain; charset=utf-84267http://localhost:8080/xmlui/bitstream/20.500.12008/31504/5/license.txt6429389a7df7277b72b7924fdc7d47a9MD55CC-LICENSElicense_urllicense_urltext/plain; charset=utf-850http://localhost:8080/xmlui/bitstream/20.500.12008/31504/2/license_urla006180e3f5b2ad0b88185d14284c0e0MD52license_textlicense_texttext/html; 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- Universidad de la Repúblicafalse |
| spellingShingle | Travel time estimation in public transportation using bus location data Massobrio, Renzo Travel time public transportation Data analysis GPS data |
| status_str | submittedVersion |
| title | Travel time estimation in public transportation using bus location data |
| title_full | Travel time estimation in public transportation using bus location data |
| title_fullStr | Travel time estimation in public transportation using bus location data |
| title_full_unstemmed | Travel time estimation in public transportation using bus location data |
| title_short | Travel time estimation in public transportation using bus location data |
| title_sort | Travel time estimation in public transportation using bus location data |
| topic | Travel time public transportation Data analysis GPS data |
| url | https://hdl.handle.net/20.500.12008/31504 |
