The digital networking of people, infrastructure and mobility carriers enables innovative solutions that sustainably change conventional mobility. Intelligent networking and big-data analytics can optimize the mobility parameters of road users and systems, as well as the mobility environment as a whole. Autonomous cars require a real-time understanding of the environment, the ability to adapt to a wide variety of conditions and the exchange of information about road users.
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Leibniz AI Academy
Development and establishment of a transcurricular, cross-disciplinary micro-degree program "Leibniz AI Academy" at Leibniz Universität Hannover (LUH).
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Model predictive control for reactive traffic control
Investigating suitable MPC appraoches to emulate a reactive environment for testing AVs in different scenarios.
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Zukunftslabor “Mobilität” (Future Lab “Mobility”)
In the Future Lab (Zukunftslabor Mobility, L3S investigates communication-based fusion of sensor data of different vehicles to achieve a collective perception.
