  The operation of groups of heavy-duty vehicles (HDVs) at a small
inter-vehicular distance (known as platoon) allows to lower the overall
aerodynamic drag and, therefore, to reduce fuel consumption and greenhouse gas
emissions. However, due to the large mass and limited engine power of HDVs,
slopes have a significant impact on the feasible and optimal speed profiles
that each vehicle can and should follow. Therefore maintaining a short
inter-vehicular distance as required by platooning without coordination between
vehicles can often result in inefficient or even unfeasible trajectories. In
this paper we propose a two-layer control architecture for HDV platooning aimed
to safely and fuel-efficiently coordinate the vehicles in the platoon. Here,
the layers are responsible for the inclusion of preview information on road
topography and the real-time control of the vehicles, respectively. Within this
architecture, dynamic programming is used to compute the fuel-optimal speed
profile for the entire platoon and a distributed model predictive control
framework is developed for the real-time control of the vehicles. The
effectiveness of the proposed controller is analyzed by means of simulations of
several realistic scenarios that suggest a possible fuel saving of up to 12%
for the follower vehicles compared to the use of standard platoon controllers.
