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Integration of visible light communication, artificial intelligence, and rerouting strategies for enhanced urban traffic management

2024-12-11Journal article Open access
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dc.contributor.authorVieira, Manuela
dc.contributor.authorGalvão, Gonçalo
dc.contributor.authorVieira, Manuel Augusto
dc.contributor.authorVéstias, Mário
dc.contributor.authorVieira, Pedro
dc.contributor.authorLouro, Paula
dc.date.accessioned2025-01-07T08:45:34Z
dc.date.available2025-01-07T08:45:34Z
dc.date.issued2024-12-11
dc.description.abstractThis study combines Visible Light Communication (VLC) and Artificial Intelligence (AI) to enhance traffic signal control, reduce congestion, and improve safety, through real-time monitoring and dynamic traffic management. Leveraging VLC technology, the system uses existing road infrastructure to transmit live data on vehicle and pedestrian positions, speeds, and queues. AI agents, employing Deep Reinforcement Learning (DRL), process this data to manage traffic flows dynamically, applying anti-bottleneck and rerouting techniques to balance pedestrian and vehicle waiting times. A centralized global agent coordinates the local agents controlling each intersection,enabling indirect communication and data sharing to train a unified DRL model. This model makes real-time adjustments to traffic light phases, utilizing a queue/request/response system for adaptive intersection management. Tested using simulations and real-world trials involving standard and rerouting scenarios, the approach demonstrates significantly better performance in regard to the rerouting configuration, reducing congestion and enhancing traffic flow and pedestrian safety.Scalable and adaptable to various intersection types, including four-way, T-intersections, and roundabouts, the system’s efficacy is validated using the SUMO urban mobility simulator, resulting in notable reductions to travel and waiting times for both vehicles and pedestrians.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationVieira M, Galvão G, Vieira MA, Véstias M, Vieira P, Louro P. Integration of Visible Light Communication, Artificial Intelligence, and Rerouting Strategies for Enhanced Urban Traffic Management. Vehicles. 2024; 6(4):2106-2132. https://doi.org/10.3390/vehicles6040103pt_PT
dc.identifier.doi10.3390/vehicles6040103pt_PT
dc.identifier.eissn2624-8921
dc.identifier.urihttp://hdl.handle.net/10400.21/18121
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationCentre of Technology and Systems
dc.relation.publisherversionhttps://www.mdpi.com/2624-8921/6/4/103pt_PT
dc.subjectvisible light communication (VLC)pt_PT
dc.subjectdeep reinforcement learning (DRL)pt_PT
dc.subjecttraffic signal optimizationpt_PT
dc.subjectconnected vehicles (CVs)pt_PT
dc.subjectmulti-agent systemspt_PT
dc.subjecturban traffic managementpt_PT
dc.subjectqueue/request/ response methodologypt_PT
dc.subjecttraffic flow simulationpt_PT
dc.titleIntegration of visible light communication, artificial intelligence, and rerouting strategies for enhanced urban traffic managementpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre of Technology and Systems
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00066%2F2020/PT
oaire.citation.endPage2132pt_PT
oaire.citation.issue4pt_PT
oaire.citation.startPage2106pt_PT
oaire.citation.titleVehiclespt_PT
oaire.citation.volume6pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameVieira
person.familyNameAugusto Vieira
person.familyNameVéstias
person.familyNameVieira
person.familyNameLouro
person.givenNameManuela
person.givenNameManuel
person.givenNameMário
person.givenNamePedro
person.givenNamePaula
person.identifier10792
person.identifierI-8527-2018
person.identifier499161
person.identifier.ciencia-id9516-E25E-BB8E
person.identifier.ciencia-idA511-1330-549F
person.identifier.ciencia-id4717-C2C7-3F2C
person.identifier.ciencia-id071B-9A70-15B8
person.identifier.ciencia-idE511-8C08-E606
person.identifier.orcid0000-0002-1150-9895
person.identifier.orcid0000-0003-1385-3646
person.identifier.orcid0000-0001-8556-4507
person.identifier.orcid0000-0003-0279-8741
person.identifier.orcid0000-0002-4167-2052
person.identifier.ridV-7860-2017
person.identifier.ridH-9953-2012
person.identifier.ridU-8346-2017
person.identifier.scopus-author-id7202140173
person.identifier.scopus-author-id5719 1567905
person.identifier.scopus-author-id14525867300
person.identifier.scopus-author-id7004567421
person.identifier.scopus-author-id8845716400
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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