NDLI: Calibration of microscopic traffic flow models against time-series data

Content Provider	IEEE Xplore Digital Library
Author	Montanino, M. Ciuffo, B. Punzo, V.
Copyright Year	2012
Description	Author affiliation: Department of Transportation Engineering, University of Naples Federico II, Via Claudio, 21, Napoli (NA), 80125, Italy (Montanino, M.) \|\| European Commission Joint Research Centre, Institute for the Environment and Sustainability, Via E. Fermi, 2749, Ispra (VA), 21027, Italy (Ciuffo, B.) \|\| European Commission Joint Research Centre, Institute for Energy and Transport (on temporary leave from University of Naples Federico II), Via E. Fermi, 2749, Ispra (VA), 21027, Italy (Punzo, V.)
Abstract	In the field of traffic simulation, the calibration of uncertain inputs against real data is usually taken to cover the epistemic uncertainty regarding the un-modeled details of the phenomena and the aleatory not predicted by the models. For this reason, model parameters are usually indirectly derived by means of an optimization framework, which tries to maximize the fit between real and simulated measures of the traffic system. This is the case, for example, of the calibration of car-following models' parameters against vehicle trajectory data. Only recently, it has been proven that the capability of the optimization framework to provide the parameters' values that allow the car-following model reproducing real trajectories at its best is strictly connected to the setup of the optimization framework itself. This, in particular, entails the necessity to carefully choose an appropriate combination of optimization algorithm and measure of goodness of fit (GOF).
Starting Page	108
Ending Page	114
File Size	711155
Page Count	7
File Format	PDF
ISBN	9781467330640
ISSN	21530009
e-ISBN	9781467330633
e-ISBN	9781467330626
DOI	10.1109/ITSC.2012.6338686
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Calibration Optimization Data models Trajectory Vehicles Stochastic processes Linear programming
Content Type	Text
Resource Type	Article

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