  Automated driving systems are often used for lane keeping tasks. By these
systems, a local path is planned ahead of the vehicle. However, these paths are
often found unnatural by human drivers. We propose a linear driver model, which
can calculate node points that reflect the preferences of human drivers and
based on these node points a human driver preferred motion path can be designed
for autonomous driving. The model input is the road curvature. We apply this
model to a self-developed Euler-curve-based curve fitting algorithm. Through a
case study, we show that the model based planned path can reproduce the average
behavior of human curve path selection. We analyze the performance of the
proposed model through statistical analysis that shows the validity of the
captured relations.
