Calibrating Activity-based Models With External OD Information: An Overview Of Different Possibilities

Abstract

Many practitioners question the advantages of activity-based models over conventional four-step models in terms of replication of traffic counts. Therefore, in this paper, a framework is highlighted that actively links travel demand models in general, and activity-based models in particular, with traffic counts. Two approaches are presented that calibrate activity-based models with traffic counts, namely an indirect and a direct approach. The indirect approach tries to incorporate findings, based on the analysis of traffic counts, into the model components of the activity-based models. The direct approach calibrates the parameters of the travel demand model in such a way that the model replicates the observed traffic counts (quasi-)perfectly. A practical example is provided to illustrate the direct approach. The study area for this practical example is Hasselt, a Belgian city of about 70,000 residents, and its surrounding municipalities. The practical examples revealed that there is not a single roadway to success in calibrating activity-based models, but that different options exist in fine-tuning the activity-based model. Notwithstanding, it is important to recognize some open issues and avenues for further research. First, it is not always appropriate to assume that traffic counts are completely correct. Setting up some belief-structure might increase the responsiveness of the activity-based model. In addition, the OD-matrix calibration that optimizes the correspondence between estimated and observed screen-line counts could negatively impact the correspondence to other measures such as vehicle miles traveled. To conclude, formulation of a multi-objective calibration method is a key challenge for further research.