A contribution to predicting the modal split in urban passenger transport under incomplete data.

Abstract

In this paper, we propose a novel approach to estimation and prediction of the modal split of passenger urban transport under a form of data incompleteness. Researchers that have an access to micro data in the form of various household expenditures statistics can usually observe expenditures on or demand of various transport modes, including motor fuels.

But the demand or expenditures data often do not inform where motor fuels are used. Yet, for some policy analyzes (such as health impacts of transport in cities), the estimation of the split of household usage of motor fuels between urban and non-urban areas is needed.

We propose an approach, which can – based on certain assumptions – estimate this split even under the data incompleteness.