An innovative generalization method for data-driven models of steering feedback torque
Rui Zhao,
Weiwen Deng,
Kaibo Huang
et al.
Abstract:Accurately modeling steering feedback torque (SFT) is crucial for the performance of both steer-by-wire systems and driving simulators of vehicles. Physics-based methods have poor model accuracy and real-time performance, due to the model complexity and unknown or inaccurate model parameters. Therefore data-driven methods have gained increasing attention in recent years for their advantages on SFT modeling. However, developing satisfactory data-driven models requires a large amount of data with sufficient cove… Show more
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