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dc.contributor.authorHegde, Bharathkumar Shripaden
dc.contributor.authorBouroche, Melanieen
dc.date.accessioned2023-01-26T09:07:39Z
dc.date.available2023-01-26T09:07:39Z
dc.date.created25/07/2022en
dc.date.issued2022en
dc.date.submitted2022en
dc.identifier.citationBharathkumar Hegde and M?lanie Bouroche, Design of AI-based lane changing modules in connected and autonomous vehicles: a survey, Twelfth International Workshop on Agents in Traffic and Transportation, ATT 2022, Vienna, 25/07/2022, 3137, 2022en
dc.identifier.otherYen
dc.descriptionPUBLISHEDen
dc.descriptionViennaen
dc.description.abstractLane changing is one of the complex driving tasks as it requires the vehicle to be aware of its highlydynamic surrounding environment, make decisions, and enact them in a timely manner. By exploiting both sensors and inter-vehicle communication, Connected and Autonomous Vehicles (CAVs) have the potential to significantly improve lane changing safety and efficiency. The complexity of the task and the real-time requirements make lane-changing a problem particularly suited to Artificial Intelligence (AI) approaches. In this paper, we survey the design of AI-based Lane-Changing(LC) modules for CAVs. First, we identify the key factors that can influence the design of an LC module. Next, we survey recent developments in AI-based lane changing. Finally, we analyse these approaches along the dimensions of the key influencing factors and summarise the challenges that are yet to be addressed and opportunities that can guide the future developments in AI-based LC modules.en
dc.description.sponsorshipSFI Centre for Research Training in Advanced Networks for Sustainable Societies (ADVANCE CRT), Ireland under the Grant number 18/CRT/6222en
dc.language.isoenen
dc.relation.ispartofseries3137en
dc.rightsYen
dc.subjectArtificial Intelligenceen
dc.subjectMulti-agent systemsen
dc.subjectConnected and autonomous vehicle (CAV)en
dc.subjectAutonomous lane changeen
dc.subjectDeep learningen
dc.subjectIntelligent transportation systemen
dc.subject.lcshTransportationen
dc.subject.lcshArtificial Intelligenceen
dc.subject.lcshComputer Scienceen
dc.titleDesign of AI-based lane changing modules in connected and autonomous vehicles: a surveyen
dc.title.alternativeTwelfth International Workshop on Agents in Traffic and Transportationen
dc.title.alternativeATT 2022en
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/hegdeben
dc.identifier.peoplefinderurlhttp://people.tcd.ie/bourocmen
dc.identifier.rssinternalid250378en
dc.rights.ecaccessrightsopenAccess
dc.subject.TCDThemeSmart & Sustainable Planeten
dc.subject.TCDThemeTelecommunicationsen
dc.subject.TCDTagARTIFICIAL INTELLIGENCEen
dc.subject.TCDTagAutonomous lane changeen
dc.subject.TCDTagConnected and autonomous vehiclesen
dc.subject.TCDTagDistributed Systemsen
dc.subject.TCDTagMulti-agent systemsen
dc.subject.TCDTagdeep learningen
dc.identifier.rssurihttps://ceur-ws.org/Vol-3173/7.pdfen
dc.identifier.orcid_id0000-0002-2085-7867en
dc.subject.darat_thematicAccessibilityen
dc.subject.darat_thematicTransporten
dc.status.accessibleNen
dc.contributor.sponsorScience Foundation Ireland (SFI)en
dc.contributor.sponsorGrantNumber18/CRT/6222en
dc.identifier.urihttp://hdl.handle.net/2262/102027


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