Calibration of Microsimulation Models Using Nonparametric Statistical Techniques

The calibration of traffic microsimulation models has received widespread attention in transportation modeling. A recent concern is whether these models can simulate traffic conditions realistically. The recent widespread deployment of intelligent transportation systems in North America has provided an opportunity to obtain traffic-related data. In some cases the distribution of the traffic data rather than simple measures of central tendency such as the mean, is available. This paper examines a method for calibrating traffic microsimulation models so that simulation results, such as travel time, represent observed distributions obtained from the field. The approach is based on developing a statistically based objective function for use in an automated calibration procedure. The Wilcoxon rank-sum test, the Moses test and the Kolmogorov-Smirnov test are used to test the hypothesis that the travel time distribution of the simulated and the observed travel times are statistically identical. The approach is t...

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