QoS Prediction for 5G Connected and Automated Driving
This addresses safety and efficiency issues for automated vehicles in 5G V2X scenarios, but it appears incremental as it builds on existing 5G prediction capabilities.
The paper tackles the problem of sudden QoS changes affecting automated driving safety by proposing a QoS prediction scheme within 5G systems, enabling vehicles to mitigate these effects at the application level, with feasibility analyzed using a tele-operated driving use case.
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.