  We are on the cusp of a new era of connected autonomous vehicles with
unprecedented user experiences, tremendously improved road safety and air
quality, highly diverse transportation environments and use cases, as well as a
plethora of advanced applications. Realizing this grand vision requires a
significantly enhanced vehicle-to-everything (V2X) communication network which
should be extremely intelligent and capable of concurrently supporting
hyper-fast, ultra-reliable, and low-latency massive information exchange. It is
anticipated that the sixth-generation (6G) communication systems will fulfill
these requirements of the next-generation V2X. In this article, we outline a
series of key enabling technologies from a range of domains, such as new
materials, algorithms, and system architectures. Aiming for truly intelligent
transportation systems, we envision that machine learning will play an
instrumental role for advanced vehicular communication and networking. To this
end, we provide an overview on the recent advances of machine learning in 6G
vehicular networks. To stimulate future research in this area, we discuss the
strength, open challenges, maturity, and enhancing areas of these technologies.
