Adaptive Video Configuration and Bitrate Allocation for Teleoperated Vehicles

TL;DR

This paper presents an adaptive video streaming framework for teleoperated vehicles that dynamically adjusts video quality and bitrate based on network conditions to ensure reliable remote control.

Contribution

It introduces a novel framework that reconfigures multi-camera video streams in real-time considering network variability for teleoperated driving.

Findings

Improved video quality under variable network conditions

Effective real-time bitrate and resolution adaptation

Successful deployment on an actual teleoperated vehicle

Abstract

Vehicles with autonomous driving capabilities are present on public streets. However, edge cases remain that still require a human in-vehicle driver. Assuming the vehicle manages to come to a safe state in an automated fashion, teleoperated driving technology enables a human to resolve the situation remotely by a control interface connected via a mobile network. While this is a promising solution, it also introduces technical challenges, one of them being the necessity to transmit video data of multiple cameras from the vehicle to the human operator. In this paper, an adaptive video streaming framework specifically designed for teleoperated vehicles is proposed and demonstrated. The framework enables automatic reconfiguration of the video streams of the multi-camera system at runtime. Predictions of variable transmission service quality are taken into account. With the objective to improve visual quality, the framework uses so-called rate-quality models to dynamically allocate bitrates and select resolution scaling factors. Results from deploying the proposed framework on an actual teleoperated driving system are presented.