  This paper studies the value of communicated motion predictions in the
longitudinal control of connected automated vehicles (CAVs). We focus on a safe
cooperative adaptive cruise control (CACC) design and analyze the value of
vehicle-to-vehicle (V2V) communication in the presence of uncertain front
vehicle acceleration. The interest in CACC is motivated by the potential
improvement in energy consumption and road throughput. In order to quantify
this potential, we characterize experimentally the relationship between
inter-vehicular gap, vehicle speed, and (reduction of) energy consumption for a
compact plug-in hybrid electric vehicle. The resulting model is leveraged to
show efficacy of our control design, which pursues small inter-vehicle gaps
between consecutive CAVs and, therefore, improved energy efficiency. Our
proposed control design is based on a robust model predictive control framework
to systematically account for the system uncertainties. We present a set of
thorough simulations aimed at quantifying energy efficiency improvement when
vehicle states and predictions exchanged via V2V communication are used in the
control law.
