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dc.contributor.authorFigueiras, Paulo
dc.contributor.authorGonçalves, Diogo
dc.contributor.authorCosta, Ruben
dc.contributor.authorGuerreiro, Guilherme
dc.contributor.authorGeorgakis, Panos
dc.contributor.authorJardim-Gonçalves, Ricardo
dc.date.accessioned2019-07-05T11:48:20Z
dc.date.available2019-07-05T11:48:20Z
dc.date.issued2019-06-19
dc.identifier.citationFigueiras, P., Gonçalves, D., Costa, R., Guerreiro, G., Georgakis, P. and Jardim-Gonçalves, R. (2019) Novel Big Data-supported dynamic toll charging system: Impact assessment on Portugal’s shadow-toll highways, Computers & Industrial Engineering, 135(2019), pp. 476-491en
dc.identifier.issn0360-8352en
dc.identifier.doi10.1016/j.cie.2019.06.043en
dc.identifier.urihttp://hdl.handle.net/2436/622521
dc.description.abstractTraffic congestion is a huge problem in many countries. It affects not only the inner workings of cities but also the quality of life of the people that endure it. In Portugal, traffic congestion happens mainly on national/urban roads, and this phenomenon has increased since the introduction of the so called shadow-toll systems in highways that were free to use. This work proposes a toll charging system that relies on a novel dynamic congestion charging scheme, supported by state of the art Big Data technologies, in order to shift traffic from national/urban roads to tolled highways, taking into account not only the Quality of Service of the highways and national roads, but also the competitiveness of toll prices for users. This Intelligent Transportation System was tested and validated in a real-world scenario with one of the biggest freight logistics companies in Portugal and with the Portuguese public road infrastructure operator.en
dc.description.sponsorshipThis work was performed under the scope of the OPTIMUM Project - Multi-source Big Data Fusion Driven Proactivity for Intelligent Mobility, grant agreement number 636160-2, funded by the European Union's Horizon 2020 research and innovation programme.en
dc.formatapplication/PDFen
dc.languageen
dc.language.isoenen
dc.publisherElsevier BVen
dc.relation.urlhttps://www.sciencedirect.com/science/article/pii/S0360835219303742?via%3Dihuben
dc.subjectintelligent transportation systemsen
dc.subjectbig dataen
dc.subjectdynamic toll chargingen
dc.titleNovel Big Data-supported dynamic toll charging system: Impact assessment on Portugal’s shadow-toll highwaysen
dc.typeJournal articleen
dc.identifier.journalComputers & Industrial Engineeringen
dc.date.updated2019-06-25T10:43:22Z
dc.date.accepted2019-06-18
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.project636160-2en
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2020-12-19en
dc.source.volume135
dc.source.beginpage476
dc.source.endpage491
dc.description.versionAccepted version
refterms.dateFCD2019-07-05T11:47:57Z
refterms.versionFCDAM
refterms.dateFOA2019-07-05T11:48:20Z


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