ITS Korea – Statistical framework to guide traffic simulation studies

We present the results of a collaborative RTA-MASCOS research project that is working to provide (1) a methodological framework for analyzing simulation outputs, and (2) a framework to inform the design stage of a simulation study. The project aims to improve the statistical rigor and defensibility of study results. We present a high-level update of the project results that indicate the contribution this project will provide to the design, planning and evaluation of traffic simulation studies. We adapt the exploratory data analysis techniques (EDA), traditionally used in industrial quality control, to the analysis and design of traffic micro-simulations. This includes graphing the output distributions to expose the salient features, screening the data for errors, missing values and most importantly, outliers. Outlier analysis is used as a diagnostic tool to distinguish between model errors and genuine rare events. The salient features of the data revealed by EDA used to build a functional relationship between changes in the complexity of simulated network features, the range of confidence intervals, precision and simulation run size.

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