A Synthetic Population is first part of creating travel demand model by using activity-based approach. Population synthesis is application of algorithms that expanded representative samples of people or household with characterises (such as gender, car ownership, age or ethnicity etc.) to entire area of researching. Because of complexity of people decisions before or during travel, one attribute is not enough to fully describe what factors have impact on them. Population synthesis iterate a set of attributes for each person in the sample and after expansion and assigning weights create simulated people or household with their characteristic. Basic components are marginal distribution targets of household and person attributes, household and person samples and algorithm for selecting the sample records into a synthetic population such that the attributes of that population match the marginal targets. Goal of this paper is to present population synthesis and her importance for activity-based approach in travel demand modelling. The paper will consist of introduction, literature overview, presenting benefits and complexity of population synthesis, discussion and conclusion.

representative samples; set of attributes, marginal distribution, algorithm, marginal targets