A Comprehensive Rule-Based Control Strategy for Automated Lane Centering System

To address the comfort and safety concerns related to driving vehicles, the Advanced Driver Assistance System (ADAS) is gaining huge popularity. The general architecture of autonomous vehicles includes perception, planning, control, and actuation. This article aims mainly at the controls aspect of one of the emerging ADAS features Lane Centering System (LCS). Limitations in deploying this feature from a controls point of view include maintaining the lane center with winding curvatures, dealing with the dynamic environment, optimizing controls where the perception of lane boundaries is erroneous, and, finally, concurring with the driver’s preferences. Although some research is available on LCS controls, most works are related only to the lateral controls by actuating steering. To increase the robustness, a comprehensive control strategy that involves lateral control, as well as longitudinal control along with a novel strategy to select the mode of driving, is proposed. A geometric approach-based Stanley controller is used as the lateral controller because of its simplicity and robustness to disturbances. Two predictive controllers and one adaptive longitudinal controller based on road curvature, road texture, and driver’s aggressiveness are also deployed to cope with the dynamic behavior of the environment and improve the driving experience. One proportional controller is used for every predictive and adaptive controller. The performance and robustness analysis is carried out using a model-based approach in a MATLAB/Simulink simulation environment. The simulation results presented show that the proposed control strategy can achieve its objective of following complex tracks and maintaining comfort while keeping safety a priority.