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Enhancing truck platooning efficiency and safety—A distributed Model Predictive Control approach for lane-changing manoeuvres

2025-01Artigo científico Acesso aberto
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dc.contributor.authorLourenço, Beatriz
dc.contributor.authorSilvestre, Daniel
dc.contributor.institutionDEE - Departamento de Engenharia Electrotécnica e de Computadores
dc.contributor.institutionFaculdade de Ciências e Tecnologia (FCT)
dc.contributor.pblElsevier Science B.V., Amsterdam.
dc.date.accessioned2025-07-11T21:14:55Z
dc.date.available2025-07-11T21:14:55Z
dc.date.issued2025-01
dc.descriptionPublisher Copyright: © 2024 The Authors. Published by Elsevier Ltd.
dc.description.abstractThe advent of autonomous driving technologies has paved the way for notable advancements in the realm of transportation systems. This paper explores the dynamic field of truck platooning, focusing on the development of a Nonlinear Model Predictive Control (NMPC) approach within a Cooperative Adaptive Cruise Control (CACC) framework. The research tackles the critical challenges in obstacle avoidance and lane-changing manoeuvres. The core contribution of this work lies in the development and implementation of a novel NMPC algorithm tailored to platoon control. This framework integrates a penalty soft constraint to guarantee obstacle avoidance and maintain platoon coherence while optimising control inputs in real-time. Several experiments, including static and dynamic obstacle avoidance scenarios, validate the efficacy of the proposed approach. In all experiments, the vehicles closely follow one another, resulting in smooth trajectories for all system states and control input signals. Even in the event of abrupt braking by the ego vehicle, the platoon remains cohesive. Moreover, the proposed NMPC proves to be computationally efficient when compared to the state-of-the-art.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent1178771
dc.identifier.doi10.1016/j.conengprac.2024.106153
dc.identifier.issn0967-0661
dc.identifier.otherPURE: 121620966
dc.identifier.otherPURE UUID: 786fa558-f043-412f-b740-8781d5c74ff3
dc.identifier.otherScopus: 85208576575
dc.identifier.otherWOS: 001396244800001
dc.identifier.otherORCID: /0000-0002-8097-0626/work/187776954
dc.identifier.urihttp://hdl.handle.net/10362/185082
dc.identifier.urlhttps://www.scopus.com/pages/publications/85208576575
dc.language.isoeng
dc.peerreviewedyes
dc.relationFunding Information: info:eu-repo/grantAgreement/FCT/Concurso de Projetos de Investigação Científica e Desenvolvimento Tecnológico no Âmbito da Prevenção e Combate a Incêndios Florestais - 2019/PCIF%2FMPG%2F0156%2F2019/PT
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50009%2F2020/PT
dc.relationLaboratory of Robotics and Engineering Systems
dc.relationCOPELABS - Cognitive and People-centric Computing R&D Unit
dc.subjectCooperative Adaptive Cruise Control
dc.subjectNonlinear Model Predictive Control
dc.subjectObstacle avoidance
dc.subjectTruck platooning
dc.subjectControl and Systems Engineering
dc.subjectComputer Science Applications
dc.subjectElectrical and Electronic Engineering
dc.subjectApplied Mathematics
dc.titleEnhancing truck platooning efficiency and safety—A distributed Model Predictive Control approach for lane-changing manoeuvresen
dc.typejournal article
degois.publication.titleControl Engineering Practice
degois.publication.volume154
dspace.entity.typePublication
oaire.awardNumberUIDB/50009/2020
oaire.awardNumberUIDB/04111/2020
oaire.awardTitleLaboratory of Robotics and Engineering Systems
oaire.awardTitleCOPELABS - Cognitive and People-centric Computing R&D Unit
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50009%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04111%2F2020/PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublication20008e82-2b5a-447f-9cb1-a07d4ab4fb13
relation.isProjectOfPublication67639a80-0e51-4a24-9895-28ed2e7ea6e2
relation.isProjectOfPublication.latestForDiscovery67639a80-0e51-4a24-9895-28ed2e7ea6e2

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