  Computing platforms in autonomous vehicles record large amounts of data from
many sensors, process the data through machine learning models, and make
decisions to ensure the vehicle's safe operation. Fast, accurate, and reliable
decision-making is critical. Traditional computer processors lack the power and
flexibility needed for the perception and machine vision demands of advanced
autonomous driving tasks. Hardware accelerators are special-purpose
coprocessors that help autonomous vehicles meet performance requirements for
higher levels of autonomy. This paper provides an overview of ML accelerators
with examples of their use for machine vision in autonomous vehicles. We offer
recommendations for researchers and practitioners and highlight a trajectory
for ongoing and future research in this emerging field.
