Sensitivity-Based Moving Horizon Estimation of Road Friction

Environmental factors such as rain, snow, or ice significantly impact road friction, which correlates strongly with traffic safety. This work uses a sensitivity-based moving horizon estimator to gauge the maximum road friction coefficient online. The adopted friction estimation strategy combines the estimated rack force based on a linear steering system model with a nonlinear two-degree-of-freedom (DoF) single-track vehicle model. The parametric output sensitivity is monitored and integrated within the moving horizon estimation (MHE) framework to prevent an arbitrary estimate in the absence of sufficient excitation. The method is evaluated by simulations and experiments under various road conditions. The results validate the proposed strategy and demonstrate its capability to reliably estimate the maximum road friction coefficient.