Proposal of the road surface friction coefficient real-time estimation method

For Autonomous Driving (AD) system or vehicle behavior control, it is important to know the friction coefficient of the road surface accurately. It is because the lateral and the longitudinal force characteristics of the tire depend on the road surface condition largely. However, even today it is difficult to detect the tire-road friction coefficient before the deterioration of vehicle dynamics in real time. This is because the tire-road friction coefficient estimation is usually conducted by comparing the actual vehicle motion with the reference vehicle model motion. So, such conventional estimators do not perform well if there is no significant difference between the actual vehicle behavior and the model. This paper propose a method for real-time estimate tire-road friction coefficient that changes variously during driving. Using this method, the friction coefficient value for a real road can be determined from relatively simple calculations. Moreover, this method has the advantage of allowing the independent estimation of the friction coefficient value for both the front and rear wheels. In addition, this paper explain how to apply and the effect on the actual vehicle. Furthermore, we demonstrate its effectiveness via online estimation of the road surface friction coefficient based on actual vehicle experiments.