Nowadays, new technologies are pushing the road vehicle limits further. Promising applications, e.g., self-driving cars, require a suitable control system that can maintain the vehicle's stability in critical scenarios. In most of current cars, the control systems actuates independently, meaning there is not a coordination or data sharing between them. This approach can produce a conflict between these standalone controllers and thus, no improvements on the vehicle's stability are achieved or even a worse scenario can be generated. In order to overcome these problems, an integrated approach is developed in this work. This integration, defined in this work as Integrated Control (IC), is done by an intelligence coordination of all standalone controllers inside the vehicle, i.e., Anti-Lock Braking System (ABS), Electronic Stability Program (ESP) and Four-Wheel Steering System (4WS). The ABS model was built using Fuzzy logic, for which only three rules were necessary to get a good performance. To design the ESP and the 4WS, the simple handling vehicle model was used as a reference behavior. The IC was designed using the hierarchical approach with two layers, i.e., the upper and lower layer. The upper one, observes the side slip angle and depends of its value the upper layer triggers the ESP or the 4WS. Finally, in order to prove the improvements of the IC system over the non-integrated approach, a full-size vehicle model was used to perform simulation in run-off-road and mu-split scenarios.