Vehicle roll and road bank angles estimation

Driving safety can be enhanced by better understanding of risk situation, which can be achieved by the knowledge of vehicle dynamic states as well as the road geometry. Among the parameters of the road that have an influence on vehicle dynamics, one can find the bank angle, which can not however be measured by low cost onboard sensors. In this paper, a new method of road bank angle and vehicle roll estimation using an unknown input proportional integral (PI) observer is proposed. To reach this goal, first a bicycle vehicle model is chosen. This model is quite simple but well appropriate for the considered application. Thereafter, an Extended Kalman Filter (EKF) is developed in order to estimate the sideslip angle which is also difficult to measure with low cost sensors. This estimate is then used as an input of the PI observer in order to estimate vehicle roll angle and the road bank angle (road attribute). Testing on measurements obtained with a prototype vehicle shows the good behavior the proposed estimation scheme