This paper presents a MPC theory based Multi-Objective Vehicular Adaptive Cruise Control system that can comprehensively address issues of tracking capability, fuel economy and driver desired response. A hierarchical control architecture is utilized in which a lower controller compensates for nonlinear vehicle dynamics and enables tracking of desired acceleration. The upper controller is designed using model predictive control theory. A cost function is developed that considers the contradictions between tracking error, fuel consumption and driver characteristics while driver longitudinal ride comfort, driver permissible tracking range and rear-end safety are formulated as I/O constraints. Employing a "constraint softening" method to avoid computing infeasibility problems, a control law is developed and implemented using a numerical optimization algorithm. Detailed simulations show that the developed control system provides significant benefits in terms of fuel economy, vehicle safety and tracking capability while at the same time also satisfying driver desired car following characteristics.