MOnitoring, MOdeling and forecasting MObility patterns
While an established mobility modelling paradigm, based on limited data, has served us well during the past decades, currently emerging technologies provide an opportunity for a disruptive paradigm shift. Leveraging a wealth of ubiquitous, heterogeneous data that is rapidly becoming available, in conjunction with state-of-the-art modelling techniques, it is possible to model human mobility patterns at an unprecedented level of accuracy and fidelity, possibly in real-time.
Within this project, the TUM chairs of Transportation Systems Engineering (TSE) and Connected Mobility (CM) will join their complementary and interdisciplinary expertise to achieve the ambitious goals set out. In particular, we will use the expertise of CM to devise measurement systems and query infrastructure and inference models, with the aim of developing recommender systems as a possible application. Furthermore, building on previous related TSE work, we will develop behavioural mobility models, integrate (observed/inferred) demand onto a demand/supply modeling environment, and use measurements to calibrate integrated models.
Additional information can be found here.
We will leverage our network of international collaborators to obtain additional data sets and expertise, and benefit the participating researchers through international mobility research visits. The close collaboration of the interdisciplinary team is expected to result in a fruitful and long-lasting research relationship, which will lead to many other joint research activities, also following the successful completion of the MO3 project.