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Mobility of people is a result from activities such as working, shopping, sports etc. When aiming at optimizing transportation systems with respect to traffic flow, emissions and other aspects, successful and sustainable measures for improvements require large scale and detailed quantitative data about multimodal travel behavior.

The increasingly wide use of sensors of all kinds (traffic sensors, GPS, cell phone signal data, smartphone sensors, etc.) opens unprecedented opportunities for automated mobility data information processing and analysis. AIT takes advantage of this new wealth of mobility behavior data and offers cutting edge solutions for unraveling large and complex sensor datasets, including techniques for capturing travel demand of people, real-time multimodal traffic state monitoring and mobility data exploration in general to obtain new insights into spatio-temporal dependencies.


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