In order to calibrate the driver-adaptive feature, several drivers tested a wide range of parameter sets. The driver-adaptive algorithm was tuned based on the feedback by building the driver preference model, which was the correlation model between the driver characteristic indices and the preferred parameters of each driver determined through answering a questionnaire.
Today, most vehicles use an electric power steering (EPS) system as the actuator for ADAS functions such as lane-keeping assistance or an automatic parking system. The electric power steering system bears the aligning torque from the tire and the ground. A motor loading system was designed to simulate the vehicle working condition.
The lab team at Tongji University plans to use a machine-learning method to realize the adaptive functions. They will soon be conducting HIL tests for the automated driving system.