Ofer Hadar

Senior Academic

Content adaptive video compression for autonomous vehicle remote driving

Itai Dror, Raz Birman, Oren Solomon, Tomer Zehavi, Lior Taib, Amit Doran, Roee Ezra, Noui Rengenzad, Ofer Hadar

It is anticipated that in some extreme situations, autonomous cars will benefit from the intervention of a "Remote Driver". The vehicle computer may discover a failure and decide to request remote assistance for safe roadside parking. In a more extreme scenario, the vehicle may require a complete remote-driver takeover due to malfunctions or an inability to resolve unknown decision logic. In such cases, the remote driver will need a sufficiently good quality real-time video stream of the vehicle cameras to respond quickly and accurately enough to the situation at hand. Relaying such a video stream to the remote Command and Control (C&C) center is especially challenging when considering the varying wireless channel bandwidths expected in these scenarios. This paper proposes an innovative end-to-end content-sensitive video compression scheme to allow efficient and satisfactory video transmission from autonomous vehicles to the remote C&C center.

Publication language English
Publication status Published - 01.01.2021
118420Q

Keywords

Autonomous cars
Driving Simulator
HEVC
Photorealistic
Region of Interest
Remote Driver
Video Compression

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering
Access to Document
10.1117/12.2595863
Other files and links
Link to publication in Scopus