Calibration of microsimulation traffic model using neural network approach

Authors:
Irena IšToka Otković;Toma Tollazzi;Matja ŠRaml
Affiliations:
J.J. Strossmayer University of Osijek, Faculty of Civil Engineering, Drinska 16a, 31000 Osijek, Croatia;University of Maribor, Faculty of Civil Engineering, Smetanova 17, 2000 Maribor, Slovenia;University of Maribor, Faculty of Civil Engineering, Smetanova 17, 2000 Maribor, Slovenia
Venue:
Expert Systems with Applications: An International Journal
Year:
2013

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Abstract

This paper presents the results of research on the applicability of neural networks in the process of computer calibration of a microsimulation traffic model. VISSIM microsimulation model is used for calibration done at the example of roundabouts in an urban area. The calibration method is based on the prediction of a neural network for one traffic indicator, i.e. for the traveling time between measuring points. Besides the traveling time, the calibration process further/also involves a comparison between the modeled and measured queue parameters at the entrance to the intersection. The process of validation includes an analysis of traveling time and queue parameters on new sets of data gathered both at the modeled and at a new roundabout. A comparison of the traffic indicators measured in the field and those simulated with the calibrated and uncalibrated microsimulation traffic model provides an insight into the performance of the calibration procedure.