  Advancements in technology are steering attention toward creating comfortable
and acceptable driving characteristics in autonomous vehicles. Ensuring a safe
and comfortable ride experience is vital for the widespread adoption of
autonomous vehicles, as mismatches in driving styles between humans and
autonomous systems can impact passenger confidence. Current driving functions
have fixed parameters, and there is no universally agreed-upon driving style
for autonomous vehicles. Integrating driving style preferences into automated
vehicles may enhance acceptance and reduce uncertainty, expediting their
adoption. A controlled vehicle study (N = 62) was conducted with a variety of
German participants to identify the individual lateral driving behavior of
human drivers, specifically emphasizing rural roads. We introduce novel
indicators for assessing stationary and transient curve negotiation, directly
applicable in developing personalized lateral driving functions. To assess the
predictability of these indicators using self-reports, we introduce the
MDSI-DE, the German version of the Multidimensional Driving Style Inventory.
The correlation analysis between MDSI factor scores and proposed indicators
showed modest but significant associations, primarily with acceleration and
jerk statistics while the in-depth lateral driving behavior turned out to be
highly driver-heterogeneous. The dataset including the anonymized
socio-demographics and questionnaire responses, the raw vehicle measurements
including labels, and the derived driving behavior indicators are publicly
available at
https://www.kaggle.com/datasets/jhaselberger/spodb-subject-study-of-lateral-vehicle-guidance.
