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dc.contributor.author | Martí, Pasqual | es_ES |
dc.contributor.author | Jordán, Jaume | es_ES |
dc.contributor.author | Julian, Vicente | es_ES |
dc.date.accessioned | 2024-06-10T18:23:24Z | |
dc.date.available | 2024-06-10T18:23:24Z | |
dc.date.issued | 2023-08 | es_ES |
dc.identifier.issn | 0941-0643 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/204922 | |
dc.description.abstract | [EN] The modeling of fleet vehicles as self-interested agents brings a realistic perspective to open fleet transportation research. This feature allows us to model the fleet operation from a non-cooperative point of view. In this work, we study parcel delivery in a city with limited resources (roads and charging stations). We designed and implemented a system composed of a multi-agent planner and a game-theoretic coordination algorithm: a Best-Response Fleet Planner. The system allows for the self-organization of the transportation system by coordinating a fleet of self-interested electric vehicles. The system's operation is optimized together with resource usage while preserving the agents' private interests, allowing each agent to plan its actions. The results show that our system has higher scalability than similar approaches, allowing it to function for a considerable number of agents in settings that feature congestion and conflicts. Additionally, overall solution quality is improved compared to other coordination systems, reducing congestion and avoiding unnecessary waiting times. | es_ES |
dc.description.sponsorship | This work is partially supported by Grant PID2021-123673OB-C31 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe." Pasqual Marti is supported by Grant ACIF/2021/259 funded by the "Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital de la Generalitat Valenciana". Jaume Jordan is supported by Grant IJC2020-045683-I funded by MCIN/AEI/10.13039/501100011033 and by "European Union NextGenerationEU/PRTR". | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Springer-Verlag | es_ES |
dc.relation.ispartof | Neural Computing and Applications | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Intelligent agents | es_ES |
dc.subject | Transportation | es_ES |
dc.subject | Self-interest | es_ES |
dc.subject | Best response | es_ES |
dc.subject | Nash equilibrium | es_ES |
dc.subject | Coordination | es_ES |
dc.subject.classification | LENGUAJES Y SISTEMAS INFORMATICOS | es_ES |
dc.title | Best-response planning for urban fleet coordination | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1007/s00521-023-08631-9 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-123673OB-C31/ES/SERVICIOS INTELIGENTES COORDINADOS PARA AREAS INTELIGENTES ADAPTATIVAS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//ACIF%2F2021%2F259/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//IJC2020-045683-I/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica | es_ES |
dc.description.bibliographicCitation | Martí, P.; Jordán, J.; Julian, V. (2023). Best-response planning for urban fleet coordination. Neural Computing and Applications. 35(24):17599-17618. https://doi.org/10.1007/s00521-023-08631-9 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1007/s00521-023-08631-9 | es_ES |
dc.description.upvformatpinicio | 17599 | es_ES |
dc.description.upvformatpfin | 17618 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 35 | es_ES |
dc.description.issue | 24 | es_ES |
dc.relation.pasarela | S\493016 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
dc.contributor.funder | Ministerio de Educación y Ciencia e Innovación | es_ES |
dc.subject.ods | 11.- Conseguir que las ciudades y los asentamientos humanos sean inclusivos, seguros, resilientes y sostenibles | es_ES |
dc.subject.ods | 13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos | es_ES |