In this work, the authors investigate the performances of optimal allocation criteria which aims to find the best compromise between road vehicle lateral stability and minimum available adhesion on tires, by performing Steering and Active Torque Distribution corrections. Torque Vectoring allocation strategy is designed for integration on Real-Time systems, requiring modest computational and a limited set of input data, which is affordable with robust sensors that are currently installed on vehicles. Investigated solution involves a constrained double minimum least-square optimization control, which minimizes at the same time correction torques on wheels, and corresponding engaged road adhesion. Performances are assessed on standardized cornering manoeuvre test in a simulation environment. Finally, main features of the allocation strategy are evaluated with respect to a benchmark vehicle model, which also simulates complex interactions arising with on-board subsystems.