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dc.contributor.authorLinares Herreros, María Paz
dc.contributor.authorBarceló Bugeda, Jaime
dc.contributor.authorMontero Mercadé, Lídia
dc.contributor.otherFacultat d'Informàtica de Barcelona
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.date.accessioned2018-04-27T08:17:13Z
dc.date.available2018-04-27T08:17:13Z
dc.date.issued2017
dc.identifier.citationLinares, M. P., Barcelo, J., L. M. Analysis and operational challenges of dynamic ride sharing demand responsive transportation models. "Transportation Research Procedia", 2017, vol. 21, p. 110-129.
dc.identifier.issn2352-1457
dc.identifier.urihttp://hdl.handle.net/2117/116758
dc.description© <year>. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.description.abstractThere is a wide evidence that sustainable mobility is not only a technological question, automotive technology will be part of the solution as a necessary but not sufficient condition, sufficiency is emerging as a combination of a paradigm shift from car ownership to vehicle usage consequence of socio-economic changes, withthe application of Information and Communication Technologies (ICT) that make possible for a userto have access to a mobility service from anywhere to anywhere at any time. Among the many emergent mobility services Multiple Passenger Ridesharing and its variants look the more promising. However, implementations of these systems accounting specifically for time dependencies, and time windows reflecting users’ needs raise challenges in terms of real-time fleet dispatching and dynamic route calculation. On the other handthe feasibility and impacts analysis in terms of the many factors influencing the behavior of the system, as for example the service demand, the size of the service fleet, the capacity of the shared vehicles, the time windows requirements, soft or tight. This paper analyzes both aspects. The first is approached in terms of a Decision Support System whose solutions are computed in terms of ad hoc heuristics of variants of Pick Up and Delivery Problems with Time Windows and Feasibility and Profitability criteria rooted on Dynamic Insertion Heuristics. For the evaluation of the applications a Simulation Framework is proposed based on a microscopic simulation model thatemulates real-time traffic conditions and a real traffic information system, and interacts with the Decision Support System feeding it with the required data to make the decisions that are implemented in the simulation to emulate the behavior of the shared fleet. The proposed simulation framework has been implemented in a model of Barcelona’s Central Business District. The paper is completed with the discussion of the achieved results
dc.format.extent20 p.
dc.language.isoeng
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa
dc.subject.otherDemand Responsive Transport
dc.subject.otherPickup and Delivery with Time Windows
dc.subject.otherDynamic Fleet Management
dc.subject.otherMicrosopic Traffic Simulation
dc.titleAnalysis and operational challenges of dynamic ride sharing demand responsive transportation models
dc.typeArticle
dc.contributor.groupUniversitat Politècnica de Catalunya. IMP - Information Modeling and Processing
dc.identifier.doi10.1016/j.trpro.2017.03.082
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::90 Operations research, mathematical programming
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S2352146517302193
dc.rights.accessOpen Access
local.identifier.drac20325499
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MICINN//TRA2011-27791-C03-02/ES/ROBUSTEZ, RECUPERABILIDAD Y CONGESTION EN REDES DE TRANSPORTE PUBLICO/
local.citation.authorLinares, M. P.; Barcelo, J.; Montero, Lídia
local.citation.publicationNameTransportation Research Procedia
local.citation.volume21
local.citation.startingPage110
local.citation.endingPage129


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