Enhancing Vehicle Stability Through Model Predictive Control

Vehicle stability control systems have been widely and accurately cited as a significant influence in reducing the rate of severe injuries and fatalities in automotive crashes. However, these systems are purely reactive, providing additional control input only after undesired vehicle behavior is sensed. This paper presents a new approach to controlling the motion of a vehicle in highly dynamic situations. This approach solves a convex optimization problem over a finite time horizon to predict and prevent these hazardous situations. Thus, the controller determines input that simultaneously tracks the driver’s intended trajectory while preventing tire saturation. Simulation results are presented to demonstrate the efficacy of this control approach.