Machine Learning for Vehicular Networks: Recent Advances and Application Examples

Abstract

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 upcoming area.