Motion coordination of autonomous vehicles has applications from target surveillance to climate monitoring. Previous research has yielded stabilizing formation control laws for a self-propelled vehicle model with first-order rotational dynamics; however this model does not adequately describe the rotational and translational dynamics of vehicles in the atmosphere or ocean. This thesis describes the design of decentralized algorithms to control self-propelled vehicles with second-order rotational and translational dynamics. Backstepping controls for parallel and circular formations are designed in the absence of a flowfield and in a steady, uniform flowfield. Backstepping and proportional-integral controllers are then used to stabilize yaw in a rigid-body model. Feedback linearization is used to attain the desired forward speed. These formation control laws extend prior results to a more realistic vehicle model. Aside from the addition of new sensing and communication requirements, the second-order control laws are demonstrated to have comparable performance to the first-order controllers. The theoretical results are illustrated by numerical simulations.