摘要：AbstractThe recent development in micro-based transport models is a major step towards an improved understanding of transport demand and its underlying drivers. By adapting a detailed geographical resolution level and a fine-grained social description of individuals it becomes possible to investigate distribution effects across social classes and geographical spaces, elements which were not possible to take into account until recently. However, the increasing amount of details comes at a cost. As the prediction-space is enlarged, models become increasingly dependent on the quality of inputs and exogenous model assumptions of which the formation of synthetic population forecasts is by far the most important one. The paper presents a coherent description of a large-scale population synthesis framework involving all relevant steps in the synthesis stages from target harmonisation, matrix fitting, post simulation of households and agents and reweighting of the final population. The model is implemented in the Danish National Transport Model and is aimed at predicting the entire Danish population at a very detailed spatial and social level. In the paper we offer some insight with respect to the propagation of sampling noise caused by the household simulation stage and a brief validation of the model when comparing a modelled 2015 population with observed data.
