Projects

The Hi-Drive project addresses a number of key challenges which are currently hindering the progress of developments in vehicle automation. The key aim of the project is improve automated driving functions and cover a large set of traffic environments. By extending the ODD (Operational Design Domain) a higher automation level can be reached which reduces the frequency of takeover requests for the driver.

AI-SEE will develop a novel sensing technology with associated AI enabling automated driving in all relevant weather and lighting conditions (e.g. snow, heavy rain or fog) in a 24h/365-day mode. Thereby, AI-SEE will extend the Operational Design Domain (ODD) of automated vehicles and extend the technology from today’s SAE level 3 (conditional automation) to SAE level 4 (high automation) where vehicles can drive themselves with no human interaction in almost any circumstances.

In the research project KI Wissen, methods for integrating existing knowledge into the data-driven AI functions of autonomous vehicles are being developed and investigated. 
By combining conventional data-based AI methods with the knowledge-based methods developed in the project, the basis for training and validating AI functions is completely redefined.

The KI Data Tooling project will, for the first time, provide a validated database for the successful training, testing and safeguarding of AI functions for automated driving. For this purpose, real data is collected and refined, synthetic data is generated and methods for the efficient storage and utilization of these data are developed.

The project KI Delta Learning aims to develop methods and tools for the efficient extension and adaptation of existing AI modules for autonomous vehicles. The developed methods will allow for the transfer of prior knowledge to new domains or more complex scenarios. Only additional requirements, the so-called deltas, are then to be learned with minimal development effort.

In the KI Absicherung project, methods and measures are being developed to validate the safety of AI-based pedestrian detection functions. For this purpose, an exemplary argumentation is being developed to generally safeguard AI-based functions for automated driving. The results of the project should support the development of an industry consensus for an AI test strategy.

The VVM project is instrumental for the implementation of autonomous driving. Its success will have a decisive influence on the further development of this pioneering technology.

The project will develop methods to safeguard autonomous driving functions, and for the first time it will allow a quantitative assessment of the safety of these functions.

The work will use a modular approach which aims at making it possible to exchange individual components of the driving function without additional testing. On the one hand, the project therefore contributes to helping the general public better understand and accept autonomous driving and, on the other hand, it makes its implementation more easily manageable for the automotive industry.
 

L3 Pilot is the first pilot test for automated driving on the roads of Europe with the participation of all European automotive manufacturers together with partners from science and research.  100 vehicles, equipped with highly developed technology for environmental detection, will test automated systems based on SAE Levels 3 and 4 under real conditions and in a broad application in public traffic from 10 EU countries.

The „Strategy for Automated and Connected Driving“ of the Federal Government has set the goal of securing Germany's pioneering role in these technologies.  The coordination centre of VDA provides a network for industry and politics and creates a program framework for long-term strategic research and a coherent and convergent technology development.

On the Test Area of Autonomous Driving Baden-Wuerttemberg, companies and research institutes can test future-oriented technologies and services related to connected and automated driving.

Future users have the possibility to actively participate in the design and infrastructure of the test area.

The main focus of the Tech Center a-drive is the research and development of technologies for robust perception and research on the social acceptance of highly automated and autonomous driving functions.  The Tech Center creates a network of experts from different disciplines for the comprehensive problem solution.

AdaptIVe aims to leverage efficient and safe automated driving. In addition to technological aspects, the research activities focus on an ideal cooperation between the driver and the assistance system as well as on legal issues which impact successful market launch.

DENSE seeks to develop a fully reliable environment perception technology overcoming the shortcomings of current systems to sense the environment in severe weather like snow, fog and heavy rain. DENSE will lead to the needed key improvements in sensor technology – resulting in a 24/7 all-weather sensor suite – consequently enhancing the safety of automated driving.

EuroFOT is the first large-scale operational test for ADAS in Europe. The project's goal is to identify and coordinate an in-the-field testing of new Intelligent Vehicle Systems to improve the quality of European road traffic.

The vision of interactIVe is accident-free traffic realised by means of affordable integrated safety systems penetrating all vehicle classes, and thus accelerating the safety of road transport. The project develops advanced driver assistant systems (ADAS) for safer and more efficient driving. interactIVe introduces safety systems that automatically brake and steer.

RobustSENSE develops a robust and reliable sensor platform for automated and assisted driving, working in harsh environmental conditions. By combining several independent subsystems the platform leads to an integrated and comprehensive solution of a self-correcting system. Therefore, RobustSENSE will essentially contribute to enhanced road safety with a more reliable, secure and trustable sensing system.

The goal and ambition of UP-Drive is to develop an automated valet parking service for city environments, aimed at relieving a car driver from the burden of finding a parking space in city centers. Instead, the fully automated car navigates on its own through urban neighborhoods, finds a parking space and returns on-demand.

IMAGinE aims to develop new and innovative assistance systems which will support cooperative driving of the future.  Cooperative driving means that vehicles as well as traffic infrastructure are capable of interacting intelligently with each other via automated information sharing. Traffic maneuvers can thus be executed more easily.

The focus of Tech Center i-protect is the close cooperation between industry and science on vehicle safety issues and future mobility. The cooperation of the industrial partners with leading science partners in the field of passive safety results in innovative bilateral and multilateral projects and continues to create research trends in this field.

The COHERENT project aims to address the problem of exponential growth of mobile traffic and increasing network complexity by researching, developing and validating a novel control framework for future mobile networks. The key innovation of COHERENT is to develop a unified programmable control framework to coordinate the underlying heterogeneous mobile networks as a whole.

DRIVE C2X establishes a reference for cooperative driving in Europe by bringing together seven national test sites and creating a harmonized testing environment for C2X technologies. The results of this large-scale testing environment are used to raise awareness among the general public; it provides feedback for standard organisations and for initiating public-private ventures.

The simTD-project investigates the possible contribution of intelligent communication systems to improving traffic safety and mobility. It isby means of one of the world’s largest field operational tests in Germany.

TEAM advances vehicle-2-x communication technologies by LTE integration and with an automotive cloud to support decentralised traffic applications.  Taking these technologies into consideration, the project develops proactive algorithms to enable behavioural change to improve transportation networks.

UNIFY pursues an open innovation environment for telecommunication services leveraging on both networking and cloud resources. The project creates a platform for users and service providers to develop, build, deploy and operate their own rich and interconnected services.

The overall objective of the Future Study is to take a closer look at the techno-economic and societal changes due to digitization. The study covers expert and user panels and works interdisciplinary as well as cross-sectional. The results address decision-makers in politics and business alike.

You can find the Future Studies in the download section of the EICT website.

The aim of AI2Ynet is the construction and operation of a platform which enables small and medium-sized enterprises (SMEs) to apply artificial intelligence methods. In the first phase until August 2019, the concept for the setup and operation of the platform will be developed with the input of various associations and stakeholder groups.

Through cross-sector networking and linking of actors and technologies, SMEs will be supported in finding and applying suitable AI technologies. The platform should enable SMEs to handle AI components, such as data and methods of machine learning, and to develop further business scenarios and exploitation opportunities.

Industry and science are collaborating in research on key issues of the energy transition and future mobility solutions. Mobility2Grid is located on the EUREF campus in Berlin as a city district and test area of the future.

The eCo-FEV project proposes a general architecture for the integration of Fully Electric Vehicles (FEVs) into cooperative infrastructure systems and new solutions for charging.