Parameters of microscopic traffic simulation model could be calibrated using the mean error as goodness of fit. However

due to the unmatched specification of model with the granularity of data and lack of regard for the individual information

optimization algorithm might be misled to find unreasonable solutions. To deal with such issue

mesoscopic model was chosen for its simpler specification and the goodness of fit function based on the distribution of singlevehicle speed is proposed in this paper. Then

a case study was employed for calibration of simulation model by using the network of inner ring road

Guangzhou. Moreover

a traditional calibration method was used for comparison and analysis. Results show that the new measure of goodness of fit outperform the traditional one in terms of the calibration effect

parameters rationality and optimization efficiency

which reveal that the proposed method has the potential to be feasible and popularized.