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](https://www.l3s.de/wp-content/uploads/2023/04/Leibniz-AI-Academy-768x260-443x150.png)
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](https://www.l3s.de/wp-content/uploads/2023/03/project-225x150.jpg)
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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![ZUSE-KI-mobil](https://www.l3s.de/wp-content/uploads/2022/10/Logo-Zuse-KI-Mobil-300x200-225x150.jpeg)
ZUSE-KI-mobil
The ZUSE-KI-mobil project aime to develop an AI accelerator with a flexible, expandable and scalable system-on-chip (SoC) architecture.
![Zukunftslabor "Mobilität" (Future Lab "Mobility")](https://www.l3s.de/wp-content/uploads/2022/10/Bild_2022-10-25_113056561-300x225-200x150.png)
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.