Acceptance criteria for validation metrics in roadside safety based on repeated full-scale crash tests

This paper proposes acceptance criteria for quantitative comparison metrics to be applied in the Verification and Validation (V&V) process of computational models used in roadside safety. Typically, the degree of verification or validation of a numerical model is assessed by qualitatively comparing the shapes of two curves, but qualitative comparisons are subjective and open to interpretation. Using quantitative comparison metrics in the V&V process allows for an objective measure of the reliability of a numerical model. Two comparison metrics were selected from a group of 16 metrics found in the literature. Acceptance criteria suitable to the typical scatter of full-scale crash tests were established by comparing ten essentially identical vehicle redirectional crash tests. Since the tests were as identical as can be achieved experimentally, the values of the quantitative metrics represented the reasonable range for the metric corresponding to matched experiments. Typical residual errors expected in full-scale tests are also discussed.