Title:ODD-Centric Contextual Sensitivity Analysis Applied To A Non-Linear Vehicle Dynamics Model

Abstract: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.