Exploring the effects of measures of performance and calibration strategies on calibrating traffic microsimulation model: A quantitative analysis approach

Abstract

In the subject of traffic microsimulation model (TMM) calibration, measure of performance (MoP) plays an essential role. However, due to the diversity of MoP types, choosing a MoP or MoP combination (usually used for multi-criteria calibration strategy) that can represent the characteristics of field traffic operation has become the key to the calibration problem. This paper proposed a quantitative analysis approach (suitable, in general, for any TMM) with three aspects. Through this approach, more detailed and representative MoPs can be studied. At the same time, the effect of different calibration strategies with various MoP combinations on TMM calibration can also be compared comprehensively. The methodology is tested on a specific case study (a signalized link with a cyclic interrupted flow) by VISSIM, where various MoPs and calibration strategies (single-criteria, the a priori-based multi-criteria, and the a posteriori-based multi-criteria calibration strategy) are implemented for comprehensive inspection and comparison. The results show that the TMM performance is clearly dependent on the MoPs and calibration strategies. Moreover, the a posteriori-based multi-criteria calibration strategy is more stable than the other two strategies for better performance TMM. The findings of this study provide new insights into the effects of MoPs and calibration strategies on TMM calibration.