EDI coordinates the BMVI-funded project RELAI
The project RELAI - Risk Estimation with a Learning AI is funded by the Federal Ministry of Transport and Digital Infrastructure (BMVI). With our cooperation partners IPG Automotive GmbH, Fraunhofer IOSB and the University of Stuttgart, the EDI hive Framework is used to generate a catalog of synthetic test scenarios for the development of autonomous vehicles and to make them available to the public via a web portal. Here, AI algorithms evaluate real, challenging traffic situations in mixed traffic and convert them into synthetic scenarios. The main focus is on the behavior of pedestrians and cyclists in critical situations as well as the expectations of these road users on the behavior of autonomous vehicles. Another important goal is to be able to automatically calibrate different simulation environments (including a virtual reality (VR) environment) through the synthetic test scenarios. It also indicates in which areas or sections specific test scenarios can be carried out in real road tests. The automatically generated test scenarios are made accessible to the public via a web portal on the EDI hive platform. In addition, the EDI hive framework is directly linked to the mCloud, the data portal of the BMVI, so that this project also helps to build up a comprehensive mobility database in Germany. See also at Electric mobility south-west. See also at BMVI
DeepTech4Good in Stuttgart
Deeptech4Good#Stuttgart is the second business event of the DeepTech4Good Acceleration Programme and took place on 7th November 2018 in Haus der Wirtschaft, Stuttgart. Co-CEO Dr. Thomas Freudenmann and Creative Director Hitomi Fukatani presented EDI's technology at DeepTech4Goods Stuttgart on 7th November 2018. EDI was chosen as one of the finalists to present at this event (https://www.deeptechforgood.eu/ )
EDI and KAIT cooperate in making autonomous vehicles behave like good human drivers
Dynamic Risk Management: With the support of PTV, EDI and KAIT (Kanagawa Institute of Technology) work on developing and validating algorithms for autonomous vehicles that are accepted by humans and increase safety in traffic.