  The emerging vehicular networks are expected to make everyday vehicular
operation safer, greener, and more efficient, and pave the path to autonomous
driving in the advent of the fifth generation (5G) cellular system. Machine
learning, as a major branch of artificial intelligence, has been recently
applied to wireless networks to provide a data-driven approach to solve
traditionally challenging problems. In this article, we review recent advances
in applying machine learning in vehicular networks and attempt to bring more
attention to this emerging area. After a brief overview of the major concept of
machine learning, we present some application examples of machine learning in
solving problems arising in vehicular networks. We finally discuss and
highlight several open issues that warrant further research.
