  This paper presents an adaptive haptic shared control framework wherein a
driver and an automation system are physically connected through a motorized
steering wheel. The automation system is modeled as an intelligent agent that
is not only capable of making decisions but also monitoring the human's
behavior and adjusting its behavior accordingly. To enable the automation
system to smoothly exchange the control authority with the human partner, this
paper introduces a novel self-regulating impedance controller for the
automation system. To determine an optimal modulation policy, a cost function
is defined. The terms of the cost function are assigned to minimize the
performance error and reduce the disagreement between the human and automation
system. To solve the optimal control problem, we employed a nonlinear model
predictive approach and used the continuation generalized minimum residual
method to solve the nonlinear cost function. To demonstrate the effectiveness
of the proposed approach, simulation studies consider a scenario where the
human and the automation system both detect an obstacle and negotiate on
controlling the steering wheel so that the obstacle can be avoided safely. The
simulations involve four interaction modes addressing the cooperation status
(cooperative and uncooperative) and the desired direction of the control
transfer (active safety and autopilot).
