Institute for Transport Studies

MOIA Begleitforschung

  • contact:

    Dr.-Ing. Martin Kagerbauer
    M.Sc. Nadine Kostorz
    M.Sc. Gabriel Wilkes

  • funding:

    MOIA GmbH

  • Partner:

    Technische Universität München (TUM), Lehrstuhl für Verkehrstechnik

  • startdate:


  • enddate:


Mobility-On-Demand is one of the most important fields in transportation and mobility research in the recent years. Some providers of ridepooling services – such as MOIA – are already actively offering services to customers. Requests of customers with similar routes are bundled and assigned to one vehicle.. As individual travel patterns are evolving from the classic individual car-ownership to collective travel patterns including carsharing or ridepooling, it is necessary to focus on correlations between different individual mobility demands. Furthermore, mobility is increasingly influenced by national and regional or local laws and regulations. General regulations such as dynamic pricing, also need to be considered in the setup of future transportation models.

In Hamburg, MOIA currently operates a fleet of 450 electric vehicles, offering a ridepooling service which combines ride requests of different users. The accompanying research of MOIA is the first comprehensive long-term study on the implications of ridepooling services on the urban transport system. Within the first phase of the research, an empirical online-survey was carried out, gathering information of MOIA users up to now (nation wide for Germany) and non-users (in the Hamburg area) with a total of more than 12,000 successfully completed questionnaires. The survey was designed to examine the socio-demographics of users, their travel behavior as well as their evaluation of the services. The survey also included a stated choice experiment in order to analyze pricing and travel time sensitivity relating to new mobility services (such as MOIA, e-scooter, bike- and carsharing).

In the next step, a microscopic agent based travel model of the Hamburg area will be set up using mobiTopp. The model is able to represent different individual travel demand scenarios, their effects on an individual and collective level as well as their correlations with local or urban regulatory approaches. It will reflect all options for decision making within a travel chain, from the first decision to make the trip to the mode choice within the transportation system. This kind of scenario cannot sufficiently be modelled using standard conventional macroscopic traffic models, as they are only scarcely able to represent correlations on an individual level. Hence, for this accompanying research, we will especially design a custom-made, integrated, multi- and intermodal travel demand model using mobiTopp. Among the innovations of this new model, we can highlight the introduction of an new agent type “tourist” to model non-daily travel patterns as well as the coupling of mobiTopp with the fleet simulation of TU Munich.