Road Model and Vehicle State Estimation using H∞ Filter
Hajimu MASUDA, Kenichi YAMADA, Toshio ITO
It is important to estimate the road model and vehicle state for Lane Departure Warning Systems and Lane Keeping Systems. One of the conventional methods is to estimate these parameters using the Kalman filter. Recently, the H∞ filter has been derived based on H∞-theory. The H∞ filter is formulated as the robust state-estimation filter to the modeling errors and disturbances (the initial state and noises). In this paper, a estimation method of the road model and vehicle state using H∞ filter is proposed. In addition, we develop a simple method to check an existence condition of the H∞ filter per time step and a fast algorithm in case that the size of the observation vector is larger than the size of the state vector. The efficiency of the proposed methods is demonstrated by simulations.