  This paper investigates the problem of ecological driving (Eco-driving) of
vehicle platoons. To reduce the probability of a platoon stopping at red lights
and increase fuel efficiency, a two-layer control architecture is proposed. The
first layer is in charge of optimizing the leader's long-term speed profile
using traffic light and road slope information. The second layer is short-term
adaptation, in which the leader attempts to follow the planning speed profile
in real time, while the follower keeps track of the nearest preceding vehicle
and leader, to preserve the desired inter-vehicular distances. The long-term
planning is formulated as a complex optimization problem with dynamic
inequality constraints. An algorithm combining Pontryagins minimum principle
and particle swarm optimization (PSO) is established to efficiently solve the
long-term planning problem. The short-term adaptation is described as model
predictive control (MPC) problems, of which the solutions are analytically
designed. The effectiveness of the proposed algorithm is illustrated by the
simulations.
