  Four years ago, an experimental system known as PilotNet became the first
NVIDIA system to steer an autonomous car along a roadway. This system
represents a departure from the classical approach for self-driving in which
the process is manually decomposed into a series of modules, each performing a
different task. In PilotNet, on the other hand, a single deep neural network
(DNN) takes pixels as input and produces a desired vehicle trajectory as
output; there are no distinct internal modules connected by human-designed
interfaces. We believe that handcrafted interfaces ultimately limit performance
by restricting information flow through the system and that a learned approach,
in combination with other artificial intelligence systems that add redundancy,
will lead to better overall performing systems. We continue to conduct research
toward that goal.
  This document describes the PilotNet lane-keeping effort, carried out over
the past five years by our NVIDIA PilotNet group in Holmdel, New Jersey. Here
we present a snapshot of system status in mid-2020 and highlight some of the
work done by the PilotNet group.
