🤖 AI Summary
This study addresses the limitations of current 5G networks—primarily optimized for mobile broadband—in supporting large-scale remote driving, which demands high uplink bandwidth, ultra-low latency, and high reliability. The work presents the first quantitative analysis of uplink bandwidth requirements for concurrent remote driving under different 5G architectures, systematically evaluating the performance gap between edge computing (MEC)-based and centralized deployments. It further investigates the impact of duplex modes, TDD frame structures, and control channel configurations on network capacity. Findings reveal that MEC significantly enhances system scalability and that optimizing control channel allocation effectively mitigates video processing latency bottlenecks. Results demonstrate that a MEC-enabled 5G architecture is better suited for remote driving scenarios, with judicious parameter configuration substantially increasing the number of concurrently supported vehicles, thereby offering theoretical grounding and practical design guidelines for 5G-based teleoperation deployment.
📝 Abstract
Teleoperated driving (ToD) enables the remote driving or control of vehicles. For this purpose, vehicles must transmit video feeds to the ToD control center so that the remote operator is fully aware of the driving conditions and can safely control the vehicle. 5G (and beyond) networks are fundamental for the deployment of ToD as they can provide the low latency, reliable and broadband connection necessary to connect the vehicle and ToD control center. However, it is unclear whether common 5G network architectures and configurations are well-suited to support the simultaneous teleoperation of multiple vehicles with demanding uplink bandwidth, as current networks are mainly configured to support mobile broadband services. This paper demonstrates that MEC or edge-based 5G networks are better suited to support and scale the ToD service than centralized networks, and quantifies the bandwidth required to simultaneously teleoperate multiple vehicles under various 5G network architectures and configurations, including different duplexing modes and TDD frame structures. Finally, the study shows that the configuration of the control channels can help mitigate the impact that the processing time of the video feeds has on the capacity to support and scale the ToD service.