  Autonomous driving technology pledges safety, convenience, and energy
efficiency. Challenges include the unknown intentions of other road users:
communication between vehicles and with the road infrastructure is a possible
approach to enhance awareness and enable cooperation. Connected and automated
vehicles (CAVs) have the potential to disrupt mobility, extending what is
possible with driving automation and connectivity alone. Applications include
real-time control and planning with increased awareness, routing with
micro-scale traffic information, coordinated platooning using traffic signals
information, eco-mobility on demand with guaranteed parking. This paper
introduces a control and planning architecture for CAVs, and surveys the state
of the art on each functional block therein; the main focus is on techniques to
improve energy efficiency. We provide an overview of existing algorithms and
their mutual interactions, we present promising optimization-based approaches
to CAVs control and identify future challenges.
