A human driver requires a period of motor adaptation to resume normal steering after taking control of an automated vehicle.

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Low friction surfaces such as ice are challenging for drivers to navigate safely because the limited tire force capability drastically alters the vehicle dynamics compared to dry roads. Experiments on real or emulated low friction surfaces are important for testing control systems, understanding driver-vehicle interactions, and training drivers. As a way of enabling these experiments with the added flexibility of a tunable friction coefficient, this paper presents a forcebased approach to emulating the lateral dynamics of a vehicle on a low friction surface using four-wheel steer-by-wire. The steer angle commands are computed with a combination of feedforward and state feedback, and the controller explicitly handles rear wheel actuator limitations. Experimental results from an asphalt surface confirm this controller successfully tracks the lateral dynamics of the low friction reference model.

No abstract