Digital twin analysis to promote safety and security in autonomous vehicles

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dc.contributor.authorAlmeaibed, Sadeq
dc.contributor.authorAl-Rubaye, Saba
dc.contributor.authorTsourdos, Antonios
dc.contributor.authorAvdelidis, Nicolas Peter
dc.date.accessioned2021-04-12T16:22:44Z
dc.date.available2021-04-12T16:22:44Z
dc.date.issued2021-03-31
dc.description.abstractWith the new industrial revolution of digital transformation, more intelligence and autonomous systems can be adopted in the manufacturing transportation processes. Safety and security of autonomous vehicles (AVs) have obvious advantages of reducing accidents and maintaining a cautious environment for drivers and pedestrians. Therefore, the transformation to data-driven vehicles is associated with the concept of digital twin, especially within the context of AV design. This also raises the need to adopt new safety designs to increase the resiliency and security of the whole AV system. To enable secure autonomous systems for smart manufacturing transportation in an end-to-end fashion, this article presents the main challenges and solutions considering safety and security functions. This article aims to identify a standard framework for vehicular digital twins that facilitate the data collection, data processing, and analytics phases. To demonstrate the effectiveness of the proposed approach, a case study for a vehicle follower model is analyzed when radar sensor measurements are manipulated in an attempt to cause a collision. Perceptive findings of this article can pave the way for future research aspects related to employing digital twins in the AV industry.en_UK
dc.identifier.citationAlmeaibed S, Al-Rubaye S, Tsourdos A , Avdelidis NP. (2021) Digital twin analysis to promote safety and security in autonomous vehicles. IEEE Communications Standards Magazine, Volume 5, Issue 1, March 2021, pp. 40-46en_UK
dc.identifier.issn2471-2825
dc.identifier.urihttps://doi.org/10.1109/MCOMSTD.011.2100004
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16555
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectSmart manufacturingen_UK
dc.subjectIntelligent vehiclesen_UK
dc.subjectAutonomous vehiclesen_UK
dc.subjectRadaren_UK
dc.subjectDigital twinen_UK
dc.subjectAnalytical modelsen_UK
dc.titleDigital twin analysis to promote safety and security in autonomous vehiclesen_UK
dc.typeArticleen_UK

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