dc.contributor.author | Rodríguez Gutiérrez, Andrés | |
dc.contributor.author | Alonso Oreña, Borja | |
dc.contributor.author | Moura Berodia, José Luis | |
dc.contributor.author | Dell´Olio, Luigi | |
dc.contributor.other | Universidad de Cantabria | es_ES |
dc.date.accessioned | 2024-08-22T10:58:14Z | |
dc.date.available | 2024-08-22T10:58:14Z | |
dc.date.issued | 2024-10 | |
dc.identifier.issn | 2214-367X | |
dc.identifier.issn | 2214-3688 | |
dc.identifier.other | TRA2017-85853-C2-1-R | es_ES |
dc.identifier.other | PID2019-110355RB-I00 | es_ES |
dc.identifier.other | PLEC2021-007824 | es_ES |
dc.identifier.uri | https://hdl.handle.net/10902/33528 | |
dc.description.abstract | Due to the issues of land redevelopment and changes of use within urban areas, many cities must adopt measures to reorganise and optimise parking space. This paper proposes a methodology to study one of them by implementing parking information systems (PIS). This solution offers users a competitive advantage by allowing them to know about the free parking spaces at the moment of decision-making. To achieve this goal, microscopic simulations are conducted to analyse the effects of various scenarios involving the implementation of PIS. The data used in these simulations is obtained from the Santander area in Spain. For the evaluation of results, a methodology has been developed that combines the evaluation of social factors for citizens and operational impacts for decision-makers. The results show significant improvements with increasing user information rate, e. g., the number of unsuccessful parking attempts before finding a final parking space is reduced by 55%, and 37% less particulate pollutants are emitted into the atmosphere. | es_ES |
dc.description.sponsorship | The work was supported in part by: Grant PLEC2021-007824 funded by MICIU/AEI/10.13039/501100011033 and, by the European Union NextGenerationEU/PRTR. Also by the Spanish Ministerio de Ciencia e Innovación under grants TRA2017-85853-C2-1-R, PID2019- 110355RB-I00 and in part was supported by Universidad de Cantabria under grant Ayudas Predoctorares Concepción Arenal (2019) | es_ES |
dc.format.extent | 12 p. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.rights | © 2024 The Authors | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | Travel Behaviour and Society, 2024, 37, 100847 | es_ES |
dc.subject.other | Parking choice | es_ES |
dc.subject.other | Parking policies evaluation | es_ES |
dc.subject.other | Parking simulation model | es_ES |
dc.subject.other | Smart parking information system | es_ES |
dc.title | Analysis of user behavior in urban parking under different level of information scenarios provided by smart devices or connected cars | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.publisherVersion | https://doi.org/10.1016/j.tbs.2024.100847 | es_ES |
dc.rights.accessRights | openAccess | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TRA2017-85853-C2-1-R/ES/MODELO DINAMICO DE REGULACION DE LA DEMANDA DE APARCAMIENTO COMBINANDO MACRO Y MICROSIMULACION: DISEÑO Y PRUEBA PILOTO/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-110355RB-I00/ES/FORMAS INNOVADORAS DE PLANIFICACION URBANA Y DEL TRANSPORTE ANTE LOS NUEVOS SISTEMAS DE MOVILIDAD BASADOS EN LA CONDUCCION AUTONOMA | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PLEC2021-007824/ES/Next Generation Tools for advanced mobility solutions Next4Mob/ | es_ES |
dc.identifier.DOI | 10.1016/j.tbs.2024.100847 | |
dc.type.version | publishedVersion | es_ES |