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Background:Increasing computer programs and models are developed to simulate vehicle crashworthiness,dynamic, and fuel efficiency.To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively.Objective:This paper is aimed to develop objective validation metrics that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results in the form of time histories.Method and Material: This study is carried out by utilizing principal components analysis (PCA) to address multivariate correlation.Then Area Metric is applied to calculate the disagreement between two data sets presented in the type of time histories to obtain the discrepancy of the overall distribution of data.Then, time histories are translated into frequency domain for the purpose of getting the features of errors in phase, topology and magnitude.Results: The study results show thatthe values of measurements in magnitude, phase and topology are consistent with intuitive judgment based on graphics, which approves good performance of proposed metrics.Conclusions:The proposed metrics satisfy the necessary properties of ideal metric in model validation and the investigated method is capable for automotive safety applications.