This paper describes results from a case study to calibrate and evaluate of the microscopic traffic simulation model MITSIMLab, to a mixed urban-freeway network in the Brunnsviken area in the north of Stockholm under congested traffic conditions. In the absence of detailed data, only aggregate data (i.e. speed and flow measurements at sensor locations) was used to calibrate the simulation model. Two important components of the simulation model were calibrated: driving behavior models and travel behavior components, including the OD matrix and the route choice model. An optimization approach to minimize the deviation between observed and simulated measurements was used. This aggregate calibration uses simulation output, which is a result of the interaction among all components of the simulation. Therefore, it is, in general, impossible to identify the effect of individual models on traffic flow when using aggregate data. The calibration approach takes these interactions into account by iteratively calibrating the different components. The performance of the calibrated MITSIMLab model was evaluated by comparing 3 types of observed and simulated measurements: traffic flows at sensor locations, point-to-point travel times and queue lengths. A second set of measurements, taken a year after the ones used for calibration, was used in this stage. Results of the evaluation are presented. Practical difficulties and limitations that may arise with the application of the calibration and evaluation approach are discussed.