  Race cars are routinely driven to the edge of their handling limits in
dynamic scenarios well above 200mph. Similar challenges are posed in autonomous
racing, where a software stack, instead of a human driver, interacts within a
multi-agent environment. For an Autonomous Racing Vehicle (ARV), operating at
the edge of handling limits and acting safely in these dynamic environments is
still an unsolved problem. In this paper, we present a baseline controls stack
for an ARV capable of operating safely up to 140mph. Additionally, limitations
in the current approach are discussed to highlight the need for improved
dynamics modeling and learning.
