Towards Railways Remote Driving: Analysis of Video Streaming Latency and Adaptive Rate Control
Daniel Mejias, Zaloa Fernandez, Roberto Viola, Ander Aramburu, Igor Lopez, Andoni Diaz
TL;DR
This work tackles the challenge of safe, low-latency remote railway driving by proposing a streaming architecture built on 5G URLLC principles, an end-to-end latency measurement methodology for RTP-based protocols, and a three-level adaptive bitrate control that responds to RTCP metrics. The methods are validated in Vicomtech and CAF laboratories, demonstrating achievable end-to-end latencies around $L_{E2E}\approx$ 60–70 ms with sufficient bandwidth, and a S2S latency near $L_{S2S}\approx$ 150 ms; adaptive bitrate helps maintain stability at lower bandwidths, though performance degrades under severe channel attenuation. The study highlights RTSP as suitable for multi-camera remote control, complementing WebRTC for point-to-point scenarios, and points to future outdoor trials, resolution-adaptive strategies, and congestion-control enhancements to better estimate available bandwidth. Overall, the contributions provide a practical pathway toward reliable, low-latency remote driving in railway operations, with clear next steps for field deployment and protocol-level improvements.
Abstract
Remote driving aims to improve transport systems by promoting efficiency, sustainability, and accessibility. In the railway sector, remote driving makes it possible to increase flexibility, as the driver no longer has to be in the cab. However, this brings several challenges, as it has to provide at least the same level of safety obtained when the driver is in the cab. To achieve it, wireless networks and video streaming technologies gain importance as they should provide real-time track visualization and obstacle detection capabilities to the remote driver. Low latency camera capture, onboard media processing devices, and streaming protocols adapted for wireless links are the necessary enablers to be developed and integrated into the railway infrastructure. This paper compares video streaming protocols such as Real-Time Streaming Protocol (RTSP) and Web Real-Time Communication (WebRTC), as they are the main alternatives based on Real-time Transport Protocol (RTP) protocol to enable low latency. As latency is the main performance metric, this paper also provides a solution to calculate the End-to-End video streaming latency analytically. Finally, the paper proposes a rate control algorithm to adapt the video stream depending on the network capacity. The objective is to keep the latency as low as possible while avoiding any visual artifacts. The proposed solutions are tested in different setups and scenarios to prove their effectiveness before the planned field testing.