  It is widely acknowledged that drivers should remain in the control loop of
automated vehicles before they completely meet real-world operational
conditions. This paper introduces an `indirect shared control' scheme for
steer-by-wire vehicles, which allows the vehicle control authority to be
continuously shared between the driver and automation through unphysical
cooperation. This paper first balances the control objectives of the driver and
automation in a weighted summation, and then models the driver's adaptive
control behavior using a predictive control approach. The driver adaptation
modeling enables off-line evaluations of indirect shared control systems and
thus facilitates the design of the assistant controller. Unlike any
conventional driver model for manual driving, this model assumes that the
driver can learn and incorporate the controller strategy into his internal
model for more accurate path following. To satisfy the driving demands in
different scenarios, a sliding-window detector is designed to continuously
monitor the driver intention and automatically switch the authority weights
between the driver and automation. The simulation results illustrate the
advantages of considering the driver adaptation in path-following and
obstacle-avoidance tasks, and show the effectiveness of indirect shared control
for cooperative driving.
