QoS Prediction for 5G Connected and Automated Driving

TL;DR

This paper explores how 5G systems can predict and notify vehicles of QoS changes to enhance safety and efficiency in automated driving, using tele-operated driving as a case study.

Contribution

It proposes a framework for QoS prediction in 5G V2X communications and analyzes its feasibility with practical recommendations and open research directions.

Findings

Feasibility of QoS prediction in 5G V2X systems.

Use of tele-operated driving as a case study.

Identification of open research topics.

Abstract

5G communication system can support the demanding quality-of-service (QoS) requirements of many advanced vehicle-to-everything (V2X) use cases. However, the safe and efficient driving, especially of automated vehicles, may be affected by sudden changes of the provided QoS. For that reason, the prediction of the QoS changes and the early notification of these predicted changes to the vehicles have been recently enabled by 5G communication systems. This solution enables the vehicles to avoid or mitigate the effect of sudden QoS changes at the application level. This article describes how QoS prediction could be generated by a 5G communication system and delivered to a V2X application. The tele-operated driving use case is used as an example to analyze the feasibility of a QoS prediction scheme. Useful recommendations for the development of a QoS prediction solution are provided, while open research topics are identified.