  Model-based approaches have become increasingly popular in the domain of
automated driving. This includes runtime algorithms, such as Model Predictive
Control, as well as formal and simulative approaches for the verification of
automated vehicle functions. With this trend, the quality of models becomes
crucial for automated vehicle safety. Established tools from model theory which
can be applied to assure model quality are uncertainty and sensitivity analysis
[1]. In this paper, we conduct sensitivity analyses for a single and double
track vehicle dynamics model to gain insights about the models' behavior under
different operating conditions. We compare the models, point out the most
important findings regarding the obtained parameters sensitivities, and provide
examples of possible applications of the gained insights.
