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Model Predictive Control based Stability Control of Autonomous Vehicles on Low Friction Road

The challenge lies in developing fully autonomous vehicles is to drive safely in inclement weather. Driving in inclement weather is often a risky task because reacting proactively and stabilizing the vehicle on low friction road is a challenging task unlike driving on high friction road. To tackle such issue, this paper presents a predictive motion framework to operate safely on low friction road without prior knowledge of tire-road friction coefficient. The proposed control algorithm consists of the instability detection algorithm and the longitudinal/lateral motion control algorithms. The instability detection algorithm (1) determines whether the vehicle is stable without knowing friction coefficient and (2) estimates the friction coefficient. The longitudinal and lateral motion control algorithms are separately but interdependently designed based on Model Predictive Control method to proactively control the vehicle with a forecast of vehicle motions. The potential of the proposed approach is shown through computer simulations with a high fidelity vehicle model. The results show that the proposed algorithm (1) successfully reduces speed to avoid path deviation and (2) detects the vehicle instability and stabilize the vehicle due to sudden friction changes.