Robust Multirate Control Scheme With Predictive Virtual Lanes for Lane-Keeping System of Autonomous Highway Driving

In this paper, we propose a new approach for a robust multirate lane-keeping control scheme with predictive virtual lanes. First, the multirate lane-keeping control scheme is proposed to improve the lane-keeping performance and to reduce the ripple in the yaw rate. To improve the lane-keeping performance on a curved road, the integral of the lateral offset error is added to the state feedback controller. A multirate Kalman filter (KF) has been developed to resolve the problems caused by slow lane detection due to the vision processing system. This multirate KF estimates vehicle states at a fast rate using a microprocessor. Utilizing the estimated states, the linear quadratic state feedback control operates at the same fast update rate of the microprocessor. Thus, a multirate control scheme can reduce the ripple in the yaw rate. Second, we propose a virtual lane prediction method that compensates for the momentary failure of lane detection from unexpected problems. If the camera sensor momentarily fails while obtaining lane information, the predicted virtual lane can be substituted for the lane detection using the camera sensor in the proposed control scheme. Thus, the proposed control scheme can normally operate when the lane information is momentarily unavailable. The performance of the proposed method was evaluated via experiments.