Show simple item record

dc.contributor.authorCruz Piris, Luis de la 
dc.contributor.authorRivera Pinto, Diego 
dc.contributor.authorMarsá Maestre, Iván 
dc.contributor.authorHoz de la Hoz, Enrique de la 
dc.date.accessioned2017-07-27T10:00:50Z
dc.date.available2017-07-27T10:00:50Z
dc.date.issued2017-05-08
dc.identifier.bibliographicCitationCruz Piris, L., Rivera Pinto, D., Marsá Maestre, I. & Hoz de la Hoz, E. 2017, "Optimizing vehicle trips using agent negotiation through a traffic matrix”, in the 10th International Workshop on Agent-Based Complex Automated Negotiations (ACAN2017), 8-9 May 2017, Sao Paulo, Brasil
dc.identifier.urihttp://hdl.handle.net/10017/30287
dc.descriptionThe Tenth International Workshop on Agent-based Complex Automated Negotiations (ACAN2017), 08/05/2017-09/05/2017, São Paulo, Brasilen
dc.description.abstractMulti-Agent Systems (MAS) have been proved to be an effective tool to improve the efficiency of intelligent traffic control systems (using them in traffic lights scheduling, vehicle routing, etc.). Negotiation is one of the most used techniques to improve the global goal of a system while maintaining as much as possible each agent preferences. In this paper, we propose modeling the traffic characteristics produced in a transportation network during a given time interval as a traffic matrix, and then use it as core element in an agent negotiation system. We define how this matrix is generated, and the mechanisms to populate it and update it. Using the traffic matrix data, we propose to use two different selection methods to obtain a subset of agents with voting rights. The first method is based on the average speed of network edges and the second one is based on the traffic jam length for a vehicle. This subset will perform a negotiation process where other agents in the network will be proposed to block their departure or modify their departure time, to mitigate the congestion in the network edges, and as goal, reducing trip duration.en
dc.description.sponsorshipMinisterio de Economía y Competitividades_ES
dc.description.sponsorshipUniversidad de Alcaláes_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectMulti-agent systemsen
dc.subjectNegotiationen
dc.subjectTraffic matrixen
dc.titleOptimizing vehicle trips using agent negotiation through a traffic matrixen
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dc.subject.ecienciaTelecomunicacioneses_ES
dc.subject.ecienciaTelecommunicationen
dc.contributor.affiliationUniversidad de Alcalá. Departamento de Automáticaes_ES
dc.date.updated2017-07-27T08:29:50Z
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//TIN2016-80622-P/ES/Dynamic Network Agreement: negociaciones estructurales en redes complejas/DNAen
dc.relation.projectIDinfo:eu-repo/grantAgreement/UAH//CCG2016%2FEXP-048en
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//TEC2013-45183-R/ES/INTELIGENCIA COLECTIVA PARA LA NAVEGACION INTELIGENTE DE TRAFICO VEHICULAR/en
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//TIN 2014-61627-EXP/ES/DIVIDE AND NOT CONQUER-COMPORTAMIENTOS EMERGENTES EN REDES COMPLEJAS EGOISTAS/en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.identifier.uxxiCC/0000029607


Files in this item

Thumbnail

This item appears in the following Collection(s)

http://creativecommons.org/licenses/by-nc-sa/4.0/
Este ítem está sujeto a una licencia Creative Commons.