Due to the growing economy and population, traffic studies in developing countries like India are becoming more complex, which leads to a need for calibrating the developed models with more than one Measure of Effectiveness (MoE). Three MoEs have been used to calibrate the model in VISSIM, such as travel time ( \(TT\) ), vehicular speed ( \(v\) ) and acceleration (or) deceleration of each vehicle ( \(a\) ). Furthermore, minimum headway distribution ( \(h\) ) and CO2 emission data were extracted from the field for further validation. The model was calibrated using Genetic Algorithm (GA). The objective function was defined with the p-values obtained from two-sampled Kolmogorov–Smirnov test by comparing the field MoEs and the simulated MoEs. After the 93rd generation, a p-value of greater than 0.05 was obtained, indicating a good similarity between the model and the field conditions. The accuracy of all five characteristics has been verified and a satisfactory resemblance has been obtained.