  Advanced driving functions, for assistance or full automation, require strong
guarantees to be deployed. This means that such functions may not be available
all the time, like now commercially available SAE Level 3 modes that are made
available only on some roads and at law speeds. The specification of such
restriction is described technically in the Operational Design Domain (ODD)
which is a fundamental concept for the design of automated driving systems
(ADS). In this work, we focus on the example of trajectory planning and control
which are crucial functions for SAE level 4+ vehicles and often rely on
model-based methods. Hence, the quality of the underlying models has to be
evaluated with respect to the ODD. Mathematical analyses such as uncertainty
and sensitivity analysis support the quantitative assessment of model quality
in general. In this paper, we present a new approach to assess the quality of
vehicle dynamics models using an ODD-centric sensitivity analysis. The
sensitivity analysis framework is implemented for a 10-DoF nonlinear
double-track vehicle dynamics model used inside a model-predictive trajectory
controller. The model sensitivity is evaluated with respect to given ODD and
maneuver parameters. Based on the results, ODD-compliant behavior generation
strategies with the goal of minimizing model sensitivity are outlined.
