An empirical study of the effect of variable network performance on teleoperated driving

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dc.check.date2031-12-31
dc.contributor.advisorO'Driscoll, Aisling
dc.contributor.advisorSreenan, Cormac
dc.contributor.advisorexternalHines, Andrew
dc.contributor.authorJaved, Farhanen
dc.contributor.funderScience Foundation Ireland
dc.date.accessioned2026-09-28T13:02:46Z
dc.date.available2026-09-28T13:02:46Z
dc.date.issued2026-03-31en
dc.date.submitted2026-03-31
dc.description.abstractThis thesis introduces an empirical study focused on the impact of variable network performance, specifically latency and packet loss, on the Quality of Experience (QoE) of remote drivers in Teleoperated Driving (ToD). In recent years, the development of 5G networks and autonomous driving systems has made significant strides. Yet, ToD remains a crucial backup for ensuring vehicle safety in complex driving scenarios that autonomous systems cannot handle. This study investigates the thresholds of network conditions beyond which ToD becomes unsafe, providing valuable insights into the relationship between network Quality of Service (QoS) and the remote driver’s experience. Utilising the TELECARLA simulator, a network-aware extension of the CARLA simulator, this thesis emulates network impairments and analyses their impact on driver performance. Key performance metrics, including Time to Collision (TTC), Steering Wheel Reversal Rate (SWRR), and subjective ratings like the Mean Opinion Score (MOS) and NASA-TLX workload assessment, are used to assess how varying network conditions influence the remote driver’s control and cognitive workload. Results reveal critical thresholds for network delays and packet loss, identifying the point at which remote driving becomes unsafe for drivers both with and without prior virtual driving experience. This research provides essential empirical data on the coupling of QoS and QoE in ToD systems, contributing to developing safe and reliable ToD frameworks. Furthermore, it offers practical guidance on how prior experience in virtual driving can help mitigate the effects of network variability, improving driver performance and safety in remote operations.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationJaved, F. 2026. An empirical study of the effect of variable network performance on teleoperated driving. MRes Thesis, University College Cork.
dc.identifier.endpage115
dc.identifier.urihttps://hdl.handle.net/10468/19344
dc.language.isoenen
dc.publisherUniversity College Corken
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/Research Centres Programme::Phase 2/13/RC/2077_P2/IE/CONNECT_Phase 2/
dc.rights© 2026, Farhan Javed.
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectTeleoperated driving
dc.subjectRemote driving
dc.subject5G & beyond networks
dc.subjectWireless communication and networks
dc.subjectQuality of Service
dc.subjectQuality of Experience
dc.subjectUser experience
dc.subjectCARLA and TELECARLA simulations
dc.subjectNext-generation telecommunication networks
dc.subjectWireless sensor networks
dc.titleAn empirical study of the effect of variable network performance on teleoperated driving
dc.typeMasters thesis (Research)en
dc.type.qualificationlevelMastersen
dc.type.qualificationnameMRes - Master of Researchen
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