Traffic network simulation has become the solution for estimating the performance of
existing and future projects. It provides this framework through the incorporation of several
driver behavior models, which through their interaction create a realistic representation
of individual drivers. As such, calibration of these sub-models is necessary to emulate
reality. In this work, two methodologies are presented that use trajectories (or derivatives,
from the Next-Generation Simulation (NGSIM) data set and a GPS study, respectively) to
perform automated calibration. The techniques for the respective calibrations are sampling
and optimization. Both methodolgies utilize Latin Hypercube Sampling, but the second
methodology is paired with a meta-heuristic optimization, called the Firefly Algorithm for
further performance improvement.
University of Minnesota M.S. thesis. September 2011. Major: Civil Engineering. Advisor: John Hourdos. 1 computer file (PDF); ix, 112 pages, appendices A-B.
Collins, Michael Bandera.
Calibration of microscopic traffic simulators using travel times and trajectories..
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