Synthesis of Robust Lane Keeping Systems: Impact of Controller and Design Parameters on System Performance

Abstract

The lane keeping system (LKS), a promising driver assistance system, is essential for autonomous vehicles. In real-world road conditions, it can be quite challenging because LKS must stay within the lane without causing passenger discomfort while both disturbances (e.g., road curvature, wind gusts, and hydroplaning) and model uncertainties in parameters [e.g., vehicle mass, center of gravity (CG), and tire cornering stiffness] are present. In this paper, the performance limits and tradeoffs between three performance criteria (lane tracking, stability robustness, and passenger comfort) are first investigated by exploring the entire design space of three prominent controllers, i.e., proportional–integral–derivative, linear–quadratic–Gaussian, and H-infinity ( $\\text{H}_{\\infty }$ ). Then, a sensitivity study on the vehicle parameters is conducted in order to investigate the impact of the parameters on the three performance metrics. Based on the aforementioned studies, this paper concludes that a robust controller can provide the maximum performance limit with respect to the lane tracking and stability robustness, when properly designed. However, it is observed that the robust controller is still sensitive to a few design and model parameters, such as look-ahead distance and CG. Therefore, the sensitivity study suggests that for vehicles with excessive mass and CG changes, such as SUVs and trucks, the adaptation of controller and look-ahead distance may be necessary to maximize both tracking performance and passenger comfort over a wide range of vehicle speeds.