TY - GEN
T1 - Adaptive Video Configuration and Bitrate Allocation for Teleoperated Vehicles
AU - Schimpe, Andreas
AU - Hoffmann, Simon
AU - Diermeyer, Frank
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85116810933&partnerID=8YFLogxK
U2 - 10.1109/IVWorkshops54471.2021.9669258
DO - 10.1109/IVWorkshops54471.2021.9669258
M3 - Conference contribution
AN - SCOPUS:85116810933
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 148
EP - 153
BT - 2021 IEEE Intelligent Vehicles Symposium Workshops, IV Workshops 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 32nd IEEE Intelligent Vehicles Symposium Workshops, IV Workshops 2021
Y2 - 11 July 2021 through 17 July 2021
ER -