New solutions

The GAIA-X 4 KI project investigates the development of a data and service ecosystem for the training and validating of artificial intelligence (AI) applications. It focuses on two use cases from the automotive industry, aiming to advance automated and connected driving as well as innovatively networked production processes. “Data” is a key player in these processes. The accumulation of data over the entire life cycle of a product and its usability for different applications could potentially lead to new forms of collaborations and value chains. The basis is the open IT infrastructure GAIA-X, which is currently being developed throughout Europe. Its decentralized organization is the foundation upon which various providers join forces and work together flexibly, while maintaining data protection, transparency and compatibility.

While the development of autonomous driving is being driven forward with great energy, the testing and safeguarding of autonomous driving functions are still very time-consuming and resource intensive. Particularly in the case of AI-supported functions, the safeguarding that accompanies development requires, among other things, enormous amounts of data that must be processed at great expense. The risk remains that not all situations that could possibly occur later when the autonomous vehicle is in operation can be covered. And yet, the AI-based decisions must be made safely and reliably at all times. This is where the SafeWahr project comes in. With the help of a continuous monitoring system, the safeguarding of an AI-based perception function in operation can be achieved. The goal is to develop a safety architecture that continuously monitors the results and decisions of the perception function and initiates the transition to a guaranteed safe state (so-called fail-operational mode) in case of relevant deviations or uncertainties.

The CiLoCharging project has set itself the goal of enabling an optimized, flexible, and demand-oriented solution for the use of electric vehicles in the distribution service of a logistics terminal from an economic, technical and ecological perspective. It takes into account the requirements from the areas of energy, logistics, charging infrastructure and mobility management. In order to be able to accurately consider the framework conditions typical for general cargo logistics, and to ensure the scalability of the fleet terminals economically, the charging management must be integrated into the existing logistics processes and also an intelligent energy management must be provided for the integration of electrified logistics terminals into the electrical distribution network.