End-to-End Teleoperated Driving Video Transmission Under 6G with AI and Blockchain

Intelligent vehicle networks powered by machine learning, AI and blockchain are transforming various sectors beyond transportation. In this context, being able to remote drive a vehicle is key for enhancing autonomous driving systems. After deploying end-to-end teleoperated driving systems under 5G networks, the need to address complex challenges in other critical areas arises. These challenges belong to different technologies that need to be integrated in this particular system: video transmission and visualization technologies, artificial intelligence techniques, and network optimization features, incorporating haptic devices and critical data security. This article explores how these technologies can enhance the teleoperated driving activity experiences already executed in real-life environments by analyzing the quality of the video which is transmitted over the network, exploring its correlation with the current state-of-the-art AI object detection algorithms, analyzing the extended reality and digital twin paradigms, obtaining the maximum possible performance of forthcoming 6G networks and proposing decentralized security schema for ensuring the privacy and safety of the end-users of teleoperated driving infrastructures. An integrated set of conclusions and recommendations will be given to outline the future teleoperated driving systems design in the forthcoming years.

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Publication Details

Journal
Sensors
Published
2026-01-14
DOI
https://doi.org/10.3390/s26020571
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
Field-Weighted Citation Impact
0.00
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article

End-to-End Teleoperated Driving Video Transmission Under 6G with AI and Blockchain

Ignacio Benito Frontelo, Marta Orduna, Pablo Pérez, Nuria Oyaga
Sensors
Vehicular Ad Hoc Networks (VANETs)
article

End-to-End Teleoperated Driving Video Transmission Under 6G with AI and Blockchain

Ignacio Benito Frontelo, Marta Orduna, Pablo Pérez, Nuria Oyaga
article en

Abstract

Intelligent vehicle networks powered by machine learning, AI and blockchain are transforming various sectors beyond transportation. In this context, being able to remote drive a vehicle is key for enhancing autonomous driving systems. After deploying end-to-end teleoperated driving systems under 5G networks, the need to address complex challenges in other critical areas arises. These challenges belong to different technologies that need to be integrated in this particular system: video transmission and visualization technologies, artificial intelligence techniques, and network optimization features, incorporating haptic devices and critical data security. This article explores how these technologies can enhance the teleoperated driving activity experiences already executed in real-life environments by analyzing the quality of the video which is transmitted over the network, exploring its correlation with the current state-of-the-art AI object detection algorithms, analyzing the extended reality and digital twin paradigms, obtaining the maximum possible performance of forthcoming 6G networks and proposing decentralized security schema for ensuring the privacy and safety of the end-users of teleoperated driving infrastructures. An integrated set of conclusions and recommendations will be given to outline the future teleoperated driving systems design in the forthcoming years.

SensorsVol. 26(2)
Nokia (Spain) (ES)
Industry, innovation and infrastructure
Openalex Percentile: Top 88%
Vehicular Ad Hoc Networks (VANETs)
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