Case · Mobility

EMDRIVE

Autonomous driving from ML scientists’ p.o.v.

Cases car headlight with code
Team
4 people
Duration
36 months
Components
Data augmentation by realistic scenario engine, AI for car control, Cloud UI to monitor the state of the Car Server
Models
AI-based data augmentation, big data engine, sensor simulation, CARLA and Autoware as simulation engines
Language
Python, Typescript, Node.js, React, C++
Tools
GPU coupling, Docker, serverless service
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Our motivation

Digitalization enables automation and networking of vehicles, which opens up an array of new mobility options. This entails a rapidly growing volume of data in the vehicle, which must be processed in near real time. The high demands on computing power, flexibility and efficiency require novel approaches in microelectronics as well as in computing and software architecture. To achieve these goals, the strategic projects of the "MANNHEIM" funding guideline as part of the "Future Fund for the Automotive Industry" will research high-performance computing platforms, innovative vehicle architectures and future-proof software development processes and methods.

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→ Questions or thoughts about AI for car control? Dr. Markus Abel and Dr. Rico Berner are looking forward to your message.

→ Looking for more information?
MANNHEIM-EMDRIVE

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