  For the optimum design of a driver-automation shared control system, an
understanding of driver behavior based on measurements and modeling is crucial
early in the development process. This paper presents a driver model through a
weighting process of visual guidance from the road ahead and haptic guidance
from a steering system for a lane-following task. The proposed weighting
process describes the interaction of a driver with the haptic guidance steering
and the driver reliance on it. A driving simulator experiment is conducted to
identify the model parameters for driving manually and with haptic guidance.
The proposed driver model matched the driver input torque with a satisfactory
goodness of fit among fourteen participants after considering the individual
differences. The validation results reveal that the simulated trajectory
effectively followed the driving course by matching the measured trajectory,
thereby indicating that the proposed driver model is capable of predicting
driver behavior during haptic guidance. Furthermore, the effect of different
degrees of driver reliance on driving performance is evaluated considering
various driver states and with system failure via numerical analysis. The model
evaluation results reveal the potential of the proposed driver model to be
applied in the design and evaluation of a haptic guidance system.
