This study proposes a calibration methodology for microscopic traffic flow simulation models that has the capability to simultaneously consider all model parameters and also to calibrate such time-dependent aspects of the model as link counts. The Simultaneous Perturbation Stochastic Approximation algorithm provides the optimization engine that determines the calibrated set of model parameters. In this study, experiments were conducted using two different CORSIM models; the results illustrate the effectiveness of the proposed calibration methodology. Current research focuses on expanding the proposed methodology to enable the simultaneous calibration of link counts, speeds, and associated bottlenecks.