  We consider the fuel-optimal coordination of trucks into platoons. Truck
platooning is a promising technology that enables trucks to save significant
amounts of fuel by driving close together and thus reducing air drag. We study
how fuel-optimal speed profiles for platooning can be computed. A first-order
fuel model is considered and pairwise optimal plans are derived. We formulate
an optimization problem that combines these pairwise plans into an overall plan
for a large number of trucks. The problem resembles a medoids clustering
problem. We propose an approximation algorithm similar to the partitioning
around medoids algorithm and discuss its convergence. The method is evaluated
with Monte Carlo simulations. We demonstrate that the proposed algorithm can
compute a plan for thousands of trucks and that significant fuel savings can be
achieved.
