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It is widely acknowledged that drivers should remain in the control loop ofautomated vehicles before they completely meet real-world operationalconditions. This paper introduces an `indirect shared control' scheme forsteer-by-wire vehicles, which allows the vehicle control authority to becontinuously shared between the driver and automation through unphysicalcooperation. This paper first balances the control objectives of the driver andautomation in a weighted summation, and then models the driver's adaptivecontrol behavior using a predictive control approach. The driver adaptationmodeling enables off-line evaluations of indirect shared control systems andthus facilitates the design of the assistant controller. Unlike anyconventional driver model for manual driving, this model assumes that thedriver can learn and incorporate the controller strategy into his internalmodel for more accurate path following. To satisfy the driving demands indifferent scenarios, a sliding-window detector is designed to continuouslymonitor the driver intention and automatically switch the authority weightsbetween the driver and automation. The simulation results illustrate theadvantages of considering the driver adaptation in path-following andobstacle-avoidance tasks, and show the effectiveness of indirect shared controlfor cooperative driving.

Indirect Shared Control of Highly Automated Vehicles for Cooperative Driving between Driver and Automation