Public private partnerships

Uniting forces to solve important AI issues

The old adage “If you want to go fast, go alone. If you want to go far, go together.” is particularly true in Artificial Intelligence. Developing AI-empowered technologies for the mobility of the future takes a lot of effort, resources and time. Additionally, the market moves very fast and there are still some big questions to be answered, and only collaboration gives us the chance to unite forces and advance AI technologies.

We are proud to bring our practical expertise in Automotive AI to the table in various Public private partnerships (PPP) together with OEMs, suppliers, technology providers, research institutes and regulators with the same passion for AI technologies.

nxtAIM – taking the next steps towards automated driving

nxtAIM utilizes the massive potential of generative technologies to develop new approaches for better scalability, transferability, and traceability of autonomous driving functions that, so far, have been very limited in their scope of use. The focus is on developing generative methods that are complementary to the established discriminative methods of artificial intelligence.

After having completed the four projects within the KI Familie project cluster, NXT GEN AI METHODS (nxtAIM) is the natural successor that aims to take the earlier findings further. Based on generative methods, introduces the bidirectional flow of information as a new paradigm into the chain of effects and enablesmassive improvements for the development of autonomous driving functions.

Dive deeper into nxtAIM’s approach and goals

Just better Data – efficient and highly accurate data generation

The Just better Data project’s aim is to create AI-driven methods and tools for gathering data efficiently and accurately. Instead of producing excessive amounts of data, the focus is on processing, evaluating, and selecting data directly on the recording vehicle's edge. AI algorithms are employed to identify missing data and fill them in with synthetic data, ensuring a fair and characteristic dataset.

Just better Data (jbDATA) is also part of the VDA initiative. Together with our partners, we want to develop and implement a Smart Data Loop to efficiently collect data relevant to training automotive AI applications, process it appropriately at the edge, and industrially utilize it. The project also explores automated anonymization ofdata, emphasizing the project’s principle of fair data generation.

Find more information on Just better Data

SafeAI - empowering safe and reliable AI engineering

SafeAI: the objective of the project is the creation of a safety argumentation for AI functions used in autonomous driving throughout the entire lifecycle.

The objective of the project is the creation of a safety argumentation for AI functions used in autonomous driving throughout the entire lifecycle. This includes the stages of planning, development, testing, deployment, monitoring and integration into the overall system. The focus is on orchestrating and interlinking the various elements of such a safety argumentation in order to demonstrate how AI functions can be permanently and reliably secured across the entire AI lifecycle.

More information on SafeAI Engineering

AIthena – building trustworthy and explainable algorithms

AUMOVIO is heavily involved in AIthena, a research and innovation project on Connected and Cooperative Automated Mobility (CCAM) solutions that aims to build trustworthy, explainable, and accountable CCAM technologies. Since they benefit from Artificial Intelligence through AI-based perception, situational awareness, and decision-making components, it’s important that the underlying technologies are trustworthy,robust, explainable and accountable.

AIthena is funded by both the European Union and the Swiss Federation.

More information on AIthena

BERTHA – making autonomous vehicles safer and more human-like

BERTHA is also an EU PPP project, in which AUMOVIO is participating. The project aims to develop a scalable and probabilistic Driver Behavioural Model (DBM) based on the Bayesian Belief Network. This model will be crucial to achieving more human-like autonomousvehicles, thus increasing road safety.

More information on BERTHA

KI Familie – tackling AI challenges in a cluster

KI Familie (AI Family) is a project cluster initiated by the VDA Leitinitiative (lead initiative by the German Association of the Automotive Industry). The initiative sets clear standards for safe autonomous driving and plays a crucial role in identifying and jointly developing important topics and action areas for the progress of autonomous vehicle functions.

It comprises of four individual projects that deal with different general issues in Automotive AI. AUMOVIO played a major role in three out of these four individual projects which have already been concluded.

KI Absicherung (AI Validation) is working on establishing a stringent and provable safety argumentation for the first time with which AI-based function modules (AI modules) can be secured and validated for highly automated driving.
KI Delta Learning (AI Delta Learning) wants to come up with methods and tools for the efficient expansion and transformation of existing AI modules in autonomous vehicles to meet the challenges of new domains or more complex scenarios.
KI Data Tooling (AI Delta Tooling) means to develop methods and tools for the generation and preparation of training, validation and safeguarding data for AI functions in autonomous vehicles.
KI Wissen (AI Knowledge), targeting methods for incorporating knowledge into machine learning.

Learn more about the KI Familie project cluster

KARLI – intelligent vehicle interaction

KARLI is the German abbreviation for „Künstliche Intelligenz für Adaptive, Responsive und Levelkonforme Interaktion im Fahrzeug der Zukunft“. By developing AI functions that detect driver states and designing interactions for different levels of automation, the project aims at providing an adaptive, responsive and level-compliant interaction in the vehicles. The project is funded by the European Union andpromoted by the German Ministry for Economic Affairs and Climate Action.

Get to know KARLI

BeIntelli – experiencing the future of mobility now

In the BeIntelli project, our AI Lab robotics team works on the Continental AMR (autonomous mobile robots) development prototype for operation in public spaces. The robot is operated by our AI-based software stack for perception, localization, and navigation as well as safety. It is the first fully automated AMR to have ever obtained a driving permission for public areas in Berlin, including the busy Kurfürstendamm and Otto-Suhr-Allee boulevards.

Supported by the German Ministry for Digital and Transport, BeIntelli is a showcase project for autonomous driving that makes it possible for everyone to experience the mobility of the future already today.

Starting with the vehicles and infrastructure of today, the project uses innovative concepts and simulation studies to seamlessly integrate advanced sensor technology into vehicles and the (road) infrastructure divided into edge areas, with local computing resources enabling decentralized processing on site. Together with a powerful AI Mobility OS, enabling the smooth interaction between the various devices, this approach will create new ecosystems for the platform economy in the mobility of the future.

Experience BeIntelli (German only)

SUNRISE – providing a safety assurance framework

The SUNRISE project is funded by the European Union and works on safety assurance of Cooperative, Connected and Automated Mobility (CCAM) systems that must be reliable in every possible driving scenario. In several initiatives, the project partners are working on developing test- and assessment methods for CCAM systems, applying a scenario-based approach, and combining both physical and virtual testing.

As well as in AIthena, AUMOVIO is continuously involved in this project.

Find out more about SUNRISE