Transport Technologies and Future Mobility


Worldwide, and to a considerable degree, passenger and freight transport contribute to global and local environmental damage and undermine quality of life, especially in urban areas. At the same time, trends can be observed that may significantly influence the way people and goods are transported in the future. These include electric transportation, the ‘sharing economy,’ and autonomous and connected driving.

Research Topics

The research group Transport Engineering and Future Mobility addresses the key issues in this context and explores the effects of current trends in light of the aforementioned challenges. Our model-based analyses with FINE.Transport assume the status quo in the transport sector, such as on the basis of transport statistics and energy balance correlations, and examine a broad spectrum of possible developments up to the year 2050 in the form of various scenarios. The parameterization of the models developed for this purpose is supported by an in-depth analysis and modeling of the decision-making behavior of mobile persons. Our Mobility Demand Simulator (MO|DE) is used for this purpose.


Dr. Thomas Grube


Building 03.2 / Room 3003

+49 2461/61-5398


Team Members

Stefan KrausBuilding 03.2 / Room 3006+49 2461/61-9842
Julian ReulBuilding 03.2 / Room 2005+49 2461/61-3079
Edgar JungblutBuilding 03.2 / Room 3009+49 2461/61-9154
Tobias OttoIngenieurswissenschaftlicher MitarbeiterBuilding 03.2 / Room 3003+49 2461/61-5398
Dipendra BhusalBuilding 03.2 / Room 3009+49 2461/61-9154
Serhiy KapustyanBuilding 03.2 / Room 34c+49 2461/61-5398

Research Area

Key features of our techno-economic optimization model, FINE.Transport, include the high spatial and temporal resolution of the observations, as well as high coverage of the relevant transport modes and propulsion options, including the associated supply infrastructures for fuels and electricity. In this manner, spatial differences in traffic patterns, including mobility behavior, can be taken into account and shift effects in the modal split and between fuel options can be investigated. With the help of the connection to the superordinate energy system model, FINE.NESTOR, coupling effects in the provision and use of energy sources can also be mapped and evaluated.

Modeling the decision-making behavior of mobile individuals within the framework of social developments is of central importance as a basis for determining transport demand. Continuous change processes, such as demographic change, accompany possible disruptive events that can be triggered, for instance, by technical developments or dynamic changes in environmental factors. In our modeling tool, MO|DE, activity-based decision models are used to map short- and long-term mobility behavior with the help of discrete choice modeling. As a result, transport demand or the modal split of transport modes are determined. The decision behavior is related to the techno-economic properties of the transport systems, such as in the area of the costs of the means of transport and the availability of refueling and charging options.

The coupling of the aforementioned models, MO|DE, FINE.Transport and FINE.NESTOR, enables the mapping of interactions between mobility behavior and the techno-economic performance of transport systems, as well as between the transport sector and other areas of the energy system. In this way, it is possible to address especially wide-ranging transport-related issues, spanning technical or techno-economic analyses, to the evaluation of political measures and the identification of cost-optimal transformation paths for the implementation of greenhouse gas-free transport systems.

Last Modified: 01.09.2023