Failures of autonomous vehicles are inevitable. One possible solution to cope with these failures is teleoperated driving, where a human operator controls the vehicle from a remote environment. In this thesis, adaptive video streaming for teleoperated driving is investigated to provide the operator with the best possible situation awareness when controlling the vehicle from remote. A teledriving framework for the adaptation of individual camera views based on the current traffic situation is developed. Additionally, a preprocessing filter concept is proposed that allows for individual rate/quality adaptation while considering the hardware limitations of autonomous vehicles.
