Designing scheme for autonomous driving of a group of vehicles is a growing field in the area of intelligent transportation systems (ITS). The idea of autonomous vehicle platooning in automated highways for optimizing the traffic and fuel, and also enhancing the safety and comfort of the passengers has a determining role in the future of transportation. To increase the efficiency and safety of traffic in this environment, a viable solution is to manage connected vehicles in groups with short inter-vehicle spaces or the so-called platoons. However a platoon-capable vehicle has many aspects to study and develop. Vehicle platooning has several advantages such as increase in road capacity, reduction of air pollution due to reduction in air resistance, and consequently less fuel consumption. It also facilitates driving with a more comfortable, and safer ride for passengers due to communication enabled driving experience and less acceleration/deceleration of the vehicle. This dissertation considers the operation of vehicles in a platoon, and studies different aspects of vehicle platooning such as establishing, maintaining and joining a platoon of vehicles. The research attempts to gain insights in the area of connected vehicles, vehicle platooning and collaborative driving. The Stability of platoon under different communication topologies is studied using the notion of input-to-state stability, and the Lyapunov- related theories. However, the main focus of this dissertation is to introduce a framework for managing and controlling connected vehicles to collaborate effectively through forming platoons, and executing different tasks such as automatic merging of multiple vehicles into a platoon and performing automated collaborative maneuvers. Several control techniques from linear and nonlinear control theory, to optimal control, and from the domain of model predictive control for both linear and nonlinear system dynamics have been implemented, and many simulation scenarios are carried out and discussed to provide a comprehensive understanding of platooning procedures and operations. The problem of vehicle platooning as autonomous vehicles with platooning capabilities is studied in the context of controlling multi-variable nonlinear systems, subject to physical and operational constraints on inputs and states. To introduce a platooning framework with multi-vehicle merging capability, the concept of optimal control and one of its practical implementations, the nonlinear model predictive control, is adopted which is a natural tool that scales well to large systems and is able to systematically handle the constraints of a nonlinear problem. To consider the effects of modeling error and measurement noise as well as estimating states using measurement data, an online estimation technique is adopted. Scenarios tested include but are not limited to one dimensional platooning, several different trajectory planning implementations with focus on smooth lateral maneuvers, multi-vehicles merging into platoon, and platooning under acceleration/deceleration of platoon leader. Several scenarios are also tested under the presence of modeling errors and measurement noise.