  Teleoperation provides human operator sophisticated perceptual and cognitive
skills into an over the network control loop. It gives hope of addressing some
challenges related to vehicular autonomy which is based on artificial
intelligence by providing a backup plan. Variable network time delays in data
transmission is the major problem in teleoperating a vehicle. On 4G network,
variability of these delays is high. Due to this, both video streaming and
driving commands encounter variable time delay. This paper presents an approach
of providing the human operator a forecast video stream which replicates future
perspective of vehicle field of view accounting the delay present in the
network. Regarding the image transformation, perspective projection technique
is combined with correction given by smith predictor in the control loop. This
image transformation accounts current time delay and tries to address both
issues, time delays as well as its variability. For experiment sake, only
frontward field of view is forecast. Performance is evaluated by performing
online vehicle teleoperation on street edge case maneuvers and later comparing
the path deviation with and without perspective projection.
