Characterizing Model Fidelity Through a Set-Based Approach

Abstract Simulation models are often used in design to predict system performance for several use cases including trade space exploration, decision-making, and validation and verification. Models are abstractions of reality and do not contain all the phenomena and details in the real world. This fact brings many concerns, such as “How can I trust this model?” or “How should I choose between models?”. In modeling and simulation (M&S), the concept of fidelity explains how a model differs from reality. This paper proposes a set-based definition of fidelity based on the reduction of information throughout the model development process. An example of a ground vehicle conducting a gradeability test demonstrates the reduction in information from reality, the known world, testing, modeling, and simulation. Overall, this set-based approach to fidelity bridges disparate definitions of fidelity and creates a greater understanding of how models reflect reality.