In research we

  • analyse the interactions between mobility behaviour, transport system, society, economy, space and the environment;
  • collect data and create methodological foundations and tools for sustainable transport planning and sustainable mobility solutions;
  • actively contribute to the dissemination of knowledge through cooperation with partners from practice and administration and through community-oriented events;
  • work with utmost diligence and integrity to achieve evidence-based results of highest quality.

Topic areas

Latest SCI publications

Latest Projects

Research project (§ 26 & § 27)
Duration : 2022-12-01 - 2023-11-30

The proposed work is intended to support the project Strategies for Resilient and Sustainable Post-COVID Passenger and Freight Mobility in the Region of Madrid (MARS MADRID 2022) of the Institute Transyt of the Universidad Politécnica de Madrid. The background of the project MARS MADRID 2022 is an analysis of the long-term impacts of the Covid-19 pandemic on mobility and transport. To address this topic mobility habits that have contributed significantly to the spread of the pandemic are studied. For this purpose, a macro-survey is carried out. Beyond the generation of knowledge and the creation of a large database, the ultimate purpose is to generate a set of guidelines for action in mobility and transport for the prevention and management of pandemics that will contribute to improving the resilience and sustainability of mobility in the Region of Madrid. The collected data are used to modify the model MARS (Metropolitan Activity Relocation Simulator) of the functional urban region Madrid. MARS is a dynamic LUTI (Land Use and Transport Interaction) model developed by Pfaffenbichler in 2003, whose basic hypothesis is that settlements and the activities that take place in them are self-organized systems (Pfaffenbichler, Emberger and Shepherd, 2008). The updated model will be used to analyse the effects of Covid-19 related phenomena like teleworking and a general aversion against mass transport. The general objective of the project MARS MADRID 2022 is to identify how the introduction of teleworking and the increase in car use will affect the general mobility of the Region of Madrid. The objective of the proposed work by BOKU is to support the abovementioned tasks of data collection and the identification, implementation and programming of the necessary changes to the model MARS. The main focus will be on data processing assessment of changes in land-use and mobility patterns due to the Covid-19 pandemic in the Madrid Region.
Research project (§ 26 & § 27)
Duration : 2022-10-24 - 2023-01-23

The focus of the project is on the development of a toolbox of methods and measures for companies for corporate mobility management (BMM) with a link to corporate health promotion (BGF). The basis and contents for this are derived from the methods and measures developed by the FGÖ in the project call "Active mobility - healthy on the road! Walking, cycling, scootering & co in everyday life" and the brochure "Active mobility - healthy on the road! Examples from practice for companies". The scientific claim is to make a generally valid categorisation and to incorporate the evaluation results from the previous project FAMOS.
Research project (§ 26 & § 27)
Duration : 2022-12-01 - 2025-11-30

The AI-CENTIVE project advances the state of the art in AI research to build and manage a complex mobility data ecosystem as enabler of intelligent applications in the context of ICT for the Future. The core innovations of AI-CENTIVE aim to support and incentivise mobility behaviour towards choosing more sustainable options, thus reducing carbon emissions from the use of private cars and petrol-/diesel-based means of transportation. Actionable datasets on mobility choices and options are currently fragmented across data silos in different organisational networks. The sharing and merging of these datasets via a common data ecosystem and its processing by Intelligent Systems - allowing for data sovereignty, security and privacy - supports the training of AI models to explain how and why citizens make certain mobility choices, and to predict their future choices based on multidimensional context parameters such as the weather, the location and duration of upcoming events or the availability of environmentally friendly options. Customised incentives leveraging AI predictions aim to motivate citizens to adopt those new options and overcome remaining barriers to more sustainable behaviour such as the need to sign up for a new service or the perceived convenience of travelling “as we have always done”. To achieve this, we need AI-based approaches to predict complex mobility behaviour and optimise incentives in a multidimensional manner, beyond currently available solutions. The project’s unique selling proposition stems from concurrently addressing a number of challenges: (i) semantically integrating heterogeneous data from multiple sources into a dynamic mobility data ecosystem; (ii) understanding the evolving data ecosystem by means of a shared mobility knowledge graph; (iii) graph-based AI algorithms to learn from user mobility behaviour and make predictions of future behaviour and propose suitable incentives, and (iv) modelling different user mobility choices based on various incentive models in order to promote the most sustainable mobility behaviour. We will make sure that our predictions are explainable and understandable so that stakeholders can make informed decisions to promote and support more sustainable behaviour in the future, thoroughly testing the results to verify and improve the approach. The results of the project will enable and incentivise Austrian citizens to find more sustainable mobility choices, increasing awareness and affecting public opinion to develop a more positive attitude towards those choices. The deployment of AI-CENTIVE algorithms as part of (i) the existing “ummadum” public mobile application to incentivise sustainable mobility choices as well as (ii) a visual analytics dashboard for professional stakeholders’ decision making will increase the visibility and uptake of project results across different target groups and guide the path to post-project exploitation.

Supervised Theses and Dissertations