The progressive urbanization has lead to an increasing complexity and relevance of mobility services. At the same time, these services are effected by long-term trends such as e-mobility and short and medium-term trends such as weather, construction sites or major events which result in challenges for traffic participants, providers of mobility services, providers of public transportation, car manufacturers and urban administration. The increasing availability of data like traffic information, or geotagged data or social media data holds great potential to be used for efficient and innovative mobility services and infrastructures. However, the existing capabilities of answering complex problems are limited, because the existing data is incomplete or is stored in isolated systems.
Data4UrbanMobility develops applications driven tools which provide an event driven overview on mobility information and enable the efficient planning, development, realization and use of innovative mobility service and thus aid administrations of cities, service providers and citizens. Based on comprehensive regional and historical data, methods from information extraction and integration respectively machine learning are applied to create profound models and predictions of traffic behavior and trends. In this fashion, specialized tools for data analytics which are integrated in a single platform which enables innovative routing and traffic management services, the adequate design and planning of infrastructures and the administration of mobility services as well for public transport as for individual traffic.