Hide metadata

dc.date.accessioned2020-07-03T18:07:49Z
dc.date.available2020-07-03T18:07:49Z
dc.date.created2019-07-03T09:55:10Z
dc.date.issued2019
dc.identifier.citationTong, Wang Hussain, Azhar Bo, Wang Xi Maharjan, Sabita . Artificial Intelligence for Vehicle-To-Everything: A Survey. IEEE Access. 2019, 7, 10823-10843
dc.identifier.urihttp://hdl.handle.net/10852/77441
dc.description.abstractRecently, the advancement in communications, intelligent transportation systems, and computational systems has opened up new opportunities for intelligent traffic safety, comfort, and efficiency solutions. Artificial intelligence (AI) has been widely used to optimize traditional data-driven approaches in different areas of the scientific research. Vehicle-to-everything (V2X) system together with AI can acquire the information from diverse sources, can expand the driver's perception, and can predict to avoid potential accidents, thus enhancing the comfort, safety, and efficiency of the driving. This paper presents a comprehensive survey of the research works that have utilized AI to address various research challenges in V2X systems. We have summarized the contribution of these research works and categorized them according to the application domains. Finally, we present open problems and research challenges that need to be addressed for realizing the full potential of AI to advance V2X systems.
dc.languageEN
dc.titleArtificial Intelligence for Vehicle-To-Everything: A Survey
dc.typeJournal article
dc.creator.authorTong, Wang
dc.creator.authorHussain, Azhar
dc.creator.authorBo, Wang Xi
dc.creator.authorMaharjan, Sabita
cristin.unitcode185,15,5,71
cristin.unitnameDigitale infrastrukturer og sikkerhet
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin1709658
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=IEEE Access&rft.volume=7&rft.spage=10823&rft.date=2019
dc.identifier.jtitleIEEE Access
dc.identifier.volume7
dc.identifier.startpage10823
dc.identifier.endpage10843
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2019.2891073
dc.identifier.urnURN:NBN:no-80574
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn2169-3536
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/77441/1/Artificial%2BIntelligence%2Bfor%2BVehicle-to-Everything.pdf
dc.type.versionPublishedVersion


Files in this item

Appears in the following Collection

Hide metadata