Realistic Field Trial Evaluation of a Tele-operated Support Service for Remote Driving over 5G

Kakkavas, Grigorios; Diamanti, Maria; Nyarko, Kwame Nseboah; Gabriel, Matthias; Karyotis, Vasileios; Mosner, Klaus; Papavassiliou, Symeon

doi:10.1109/cscn57023.2022.10051034

Cited by 1 publication

(1 citation statement)

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“…The tests focused on measuring the mean latency, mean throughput, jitter, and loss rate for each data stream exchanged between the ROC and the ROC-GW node installed within the vehicle. To this end, the incoming and outgoing traffic at the ROC-GW and ROC measurement points were captured and postprocessed [11].…”

Section: A Experimental Setup and Validation Trialsmentioning

confidence: 99%

5G Perspective Of Connected Autonomous Vehicles: Current Landscape and Challenges Toward 6G

Kakkavas,

Diamanti,

Karyotis

et al. 2024

IEEE Wireless Commun.

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Connected and Autonomous Vehicles (CAVs) have emerged as a promising paradigm in the automotive industry, revolutionizing transportation systems with their potential to improve safety, efficiency, and overall user experience. The communication aspect of CAVs is vital to enable their advanced capabilities. In this article, we focus on analyzing the current landscape, challenges, and future vision of CAVs from a 5G perspective. Unlike previous theoretical studies, our approach is grounded on empirical evidence obtained through trials conducted over a commercial 5G deployment, considering two representative use cases: "Remote Driving" and "Quality of Service (QoS)-based Level-of-Automation Selection". Based on the quantitative findings, we identify and discuss several open challenges that need to be overcome to seamlessly integrate CAVs into the 5G ecosystem. Furthermore, we outline prospective enablers for solutions and enhancements that can address the identified shortcomings and provide a solid foundation for the future of CAVs in the context of 6G. Overall, this research contributes to the ongoing efforts to optimize communication systems for CAVs, facilitating their safe and efficient integration into the future smart transportation ecosystem.

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Section: A Experimental Setup and Validation Trialsmentioning

confidence: 99%