Recent trends in automotive crash statistics suggest a dual role of technology in both saving and threatening the lives of American drivers. Advancements in automotive safety like Anti-Lock Braking Systems and Electronic Stability Control have led to a significant reduction in automotive fatalities over the last decade. However, the ubiquity of technology, mainly the cellular phone, has led to a dramatic increase in fatalities attributed to distracted driving. To address this challenge, auto manufacturers are empowering modern vehicles with even more technology. Advanced sensors provide real-time information about the surrounding environment. By-wire actuators, which allow drivers indirect command of the vehicle through an electronic pathway, enable vehicle safety systems to share control with a driver through augmentation of the driver's commands. This technology combination gives safety systems an unprecedented amount of authority to react to the vehicle's newly perceived world. Leveraging these advancements in vehicle actuation and sensing, this dissertation presents a shared control framework for obstacle avoidance and stability control using safe driving envelopes. One of these envelopes is defined by the vehicle handling limits while the other is defined by spatial limitations imposed by lane boundaries and obstacles. A Model Predictive Control (MPC) scheme determines at each time step if the current driver command allows for a safe vehicle trajectory within these two envelopes, intervening only when such a trajectory does not exist. A sparsity seeking objective in the MPC formulation serves as a simple and effective approach to shared control between a human driver and an automated machine. In this way, the controller seeks to identically match the driver's commands whenever possible while avoiding obstacles and preventing loss of control. Computationally efficient models of the environment, the vehicle, and the handling limits allow for real-time prediction of dangerous scenarios over a 4 (s) horizon. This advanced warning enables the use of brake actuation to ensure safe vehicle trajectories that adhere to both safe envelopes, providing an envelope of protection through augmentation of a driver's steering, braking, and throttle commands. The optimal control problem underlying the controller is inherently non-convex but is solved as a set of convex problems allowing for reliable, real-time implementation that is executed at 100 (Hz). This approach is validated on an experimental vehicle working with human drivers to negotiate obstacles in low friction environments.