  Neural Radiance Field (NeRF) has garnered significant attention from both
academia and industry due to its intrinsic advantages, particularly its
implicit representation and novel view synthesis capabilities. With the rapid
advancements in deep learning, a multitude of methods have emerged to explore
the potential applications of NeRF in the domain of Autonomous Driving (AD).
However, a conspicuous void is apparent within the current literature. To
bridge this gap, this paper conducts a comprehensive survey of NeRF's
applications in the context of AD. Our survey is structured to categorize
NeRF's applications in Autonomous Driving (AD), specifically encompassing
perception, 3D reconstruction, simultaneous localization and mapping (SLAM),
and simulation. We delve into in-depth analysis and summarize the findings for
each application category, and conclude by providing insights and discussions
on future directions in this field. We hope this paper serves as a
comprehensive reference for researchers in this domain. To the best of our
knowledge, this is the first survey specifically focused on the applications of
NeRF in the Autonomous Driving domain.
