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We propose a quantitative approach for calibrating and validating keyfeatures of traffic instabilities based on speed time series obtained fromaggregated data of a series of neighboring stationary detectors. We apply theproposed criteria to historic traffic databases of several freeways in Germanycontaining about 400 occurrences of congestions thereby providing a referencefor model calibration and quality assessment with respect to the spatiotemporaldynamics. First tests with microscopic and macroscopic models indicate that thecriteria are both robust and discriminative, i.e., clearly distinguishesbetween models of higher and lower predictive power.

Calibration and validation of models describing the spatiotemporal evolution of congested traffic patterns