The Generic Methodology for Verification and Validation (GM-VV) to support acceptance of models, simulations and data is a new standard under development within SISO. GM-VV provides an abstract framework to efficiently develop an argument to justify why identified models, simulations, underlying data, outcomes and capabilities are believed to be acceptable for deployment in a specific operational context. This argument is intended to support stakeholders in their acceptance decision making process on the utilization of the aforementioned Modeling and Simulation (M&S) assets for their business goals (i.e. intended purpose). GM-VV is a generic methodology which means that it is defined independently from a M&S application domain or technology. This makes the methodology generally applicable and compatible to any class of V&V problems in the M&S domain. However, this makes GM-VV also an abstract and meta-level defined methodology that has to be instantiated, specialized, extended and optimized. This is described in the GM-VV documentation. In order to apply GM-VV effectively and efficiently, a set of examples is desirable. The purpose of this paper is to present the first results of developing such an illustrative and educational example for GM-VV. The example originates from the human driving behavior research domain in which driving simulators are used to test and evaluate new technologies, procedures and policies to improve traffic safety. This example is chosen because of its relative simplicity and the availability of all needed data and information.