Problem Statement

Long-distance travel events often occur infrequently and irregularly within individual mobility patterns, but they account for a substantial share of total passenger kilometers traveled and the associated emissions. Despite its significance, long-distance travel has received considerably less attention in research on travel behavior than everyday mobility. This is mainly due to methodological challenges in capturing infrequent long-distance travel events and the lack of available data. In particular, empirical findings on long-distance travel behavior across longer observation periods at the individual level are scarce. Furthermore, existing studies usually focus exclusively on long-distance trips without considering the overall travel behavior of individuals and the interactions between everyday and long-distance travel. A deeper understanding of these interrelations, which is necessary, for example, to assess the impact of influential measures, could be achieved by considering everyday and long-distance mobility together at the individual level.

Objective

The objective of the project is to create a microscopic representation of the travel demand of the German population over a period of one year. The approach aims to consistently describe both routine everyday mobility and infrequent long-distance travel activities at the individual level.

The project seeks to provide an overview of the available data and information on individual travel behavior and to explore how these sources can be combined to generate a coherent overall picture. Based on this overview, a concept for merging the various data sources will be developed, whereby both socioeconomic characteristics and indicators of mobility behavior are to be included as linking variables. The aim is to reflect the heterogeneity of mobility behavior to a greater extent compared to earlier approaches. Furthermore, the total population will be modeled to determine the resulting overall mobility in line with key figures from official statistics.

Methods

Existing data sources on everyday and long-distance mobility are systematically compiled and analyzed for their compatibility. Based on this, a concept is developed for merging data on the everyday mobility of individuals with data on long-distance travel behavior. To support this data fusion, a supplementary survey will be conducted, specifically designed to address the linkages between the data sources.

For the extension to a one-year observation period, findings on the longitudinal behavior of individuals and the seasonality of long-distance travel events are to be taken into account. The extrapolation to the year and the total population will be carried out using key figures from official statistics.

Finally, two use cases serve to examine how well the developed model can actually reflect the heterogeneity in the mobility of individuals and how effectively the modelled travel demand can be used to evaluate the potential impacts of policy measures.