Advanced Driver Assistance Systems (ADAS) such as Lane Keeping Assistance (LKA) systems are in the focus of current vehicle developments. Of special interest is the calibration task, which plays an increasingly decisive role in early development stages. At this point it is essential to analyze the pre-calibrated controller concepts by appropriate simulation methods. A software toolchain is introduced, using Model-in-the-Loop (MiL) for the evaluation and calibration of the LKA system. Within, a Design-of-Experiment (DoE) tool is integrated together with the simulation environment. This enables the examination of the two different lateral controller concepts Steer-by-Angle (SbA) and Steer-by-Torque (SbT). Their lateral guidance performance is characterized by Key Performance Indicators (KPI), which are derived from simulation quantities of straight-line and cornering maneuvers. Further, statistical behavior models are generated based on those KPI and controller design variables (DV). The subsequent optimization process leads to high performances of both controllers. In particular, the SbA controller shows higher efficiency under the impact of disturbances as well as the reference reaction with lower settling times. Overall, the achieved lateral guidance performances indicate the potential of both control algorithms in an early development stage. With the software toolchain, a platform for further LKA system calibration and lateral guidance performance optimization is established.
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