Calibration and Validation of Microscopic Traffic Flow Models

Abstract

Since microscopic models are being heavily used in applications, the appropriate calibration and validation have been a recent concern. The contribution of this paper is to compare some of these models by calibrating and validating them with data from double-loop detectors on a multilane freeway. To simplify this task, the test of the models is done by simplifying the multilane reality to a simulation of only single lane. The results show that by simulating the multilane road with single lane models, calibration errors (Theil’s U, root mean squared error) of 14 % to 16 % can be obtained. A validation of the models –which means taking calibrated parameters of one data set to reproduce the other data sets– gives additional errors of about 0.5 to 2.5 percentage points. This is in good agreement with other calibration/validation approaches performed recently.