11. – 13. Mai 2027 | Frankfurt/Hanau
Auto[nom]Mobil
12. – 13. Mai 2027
Hier sehen Sie einen Rückblick auf das Programm des Auto[nom]Mobil 2026. Sobald das Programm der Konferenz 2027 steht, finden Sie es an dieser Stelle.
Mittwoch, 15.04.2026
Introduction TalkDr.-Ing. Michael Fausten - Technology Innovation for Complex Systems | Engineering Transformation | AI-Enabled Physical Systems; Prof. Dr.-Ing. Thomas Helmer - Technische Hochschule Ingolstadt |
Highlight MarketVorsitz: Dr.-Ing. Michael Fausten - Technology Innovation for Complex Systems | Engineering Transformation | AI-Enabled Physical Systems |
Update on Fleet L4 Operations in the USA: Robotaxis and TruckingRichard Bishop - Next Generation Mobility LLC
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Start-up PitchesVorsitz: Dr.-Ing. Michael Fausten - Technology Innovation for Complex Systems | Engineering Transformation | AI-Enabled Physical Systems |
Hyper-Realistic Simulation for Future Radar DevelopmentsDr.-Ing. Michael Stelzig - fiveD GmbH |
Enhancing InCabin Safety While Saving Cost, by Using High-res 4D Imaging RadarIan Podkamien - VAYYAR automotive |
Operation of L4Vorsitz: Prof. Dr.-Ing. Günther Prokop - Technische Universität Dresden |
Crossing a Public Road With a Heavy Automated Guided Vehicle (AGV) - Closing the Regulatory Gap Between AFGBV and Exemption From Registration for Vehicles With Maximum Design Speed of up to 6 km/hUdo Steininger, Walter Dasch - TESACO GmbH; Jonas Herde - TÜV SÜD
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Start-up Pitches |
Introduction of Kontrol |
How Safe is Safe? - Chinese and European PerspectivesVorsitz: Udo Steininger - TESACO GmbH |
SOTIF Index and Its Role on V&V for Autonomous DrivingProf. Hong Wang - Tsinghua University
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AI-SAP - Automobile Intelligent Safety Assessment ProgrammeFan Hailong - China Merchants Vehicle Research (CMVR)
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Public Perception of Automated Driving: Results of a European SurveyDr. Michael Praxenthaler - Allianz Zentrum für Technik (AZT)
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Closing the Gap - From Legislation to TestingVorsitz: Dr.-Ing. Thomas Stäblein - Mercedes-Benz AG |
Mobility and Structural Change. A Project in the Free State of Saxony.Michael Stritzke - Sächsisches Staatsministerium für Infrastruktur und Landesentwicklung
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Current Developments in Legislation for Autonomous Driving, Scenario Database, and Virtual Testing in the Context of the EU/UNECESven Paeslack - Kraftfahrt-Bundesamt
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SYNERGIES: A European Scenario Dataspace for Safety Validation of CCAM SystemsHenrik Liers - Verkehrsunfallforschung an der TU Dresden GmbH
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European SCART-Institute: Scenario-based Type Approval Processes in Europe – Current Status and OutlookProf. Dr.-Ing. Günther Prokop - Technische Universität Dresden |
Wrap Up Day 1Dr.-Ing. Michael Fausten - Technology Innovation for Complex Systems | Engineering Transformation | AI-Enabled Physical Systems |
Donnerstag, 16.04.2026
Setting the Scene - Responsibilities in the Operation of Automated VehiclesVorsitz: Prof. Dr.-Ing. Thomas Helmer - Technische Hochschule Ingolstadt |
Who is Liable – Owner Liability vs. Manufacturer LiabilityDr. Martin Stadler - Allianz Versicherungs-AG
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Managing Complex ADAS – User Perspectives & Challenges to Proof Regulatory ComplianceDr. Norbert Schneider - Würzburger Institut für Verkehrswissenschaften (WIVW GmbH)
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Safety Starts with Information - Perception TechnologyVorsitz: Florian Ehrenberg - Magna Electronics Germany GmbH |
Interior Sensing AI for in-cabin Safety & Health MonitoringDr.-Ing. Oliver Lange - Robert Bosch GmbH
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In-Cabin Sensing Technologies Transforming Safety, Comfort, and Regulatory Compliance In Modern VehicleDr. Sylvie Wacquant - Magna Electronics
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Context-Aware ADAS: Integrating Interior Sensing Outputs Into ADAS/AD for Safe DrivingAmit Bhandare - Magna Electronics
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Radar Next Level: A Modern Paradigm for Perception in High DefinitionDr. Axel Schwarz - Robert Bosch GmbHFor decades, automotive radar has been limited by a rigid processing pipeline that forces complex sensor data into a sparse point cloud, creating an irreversible information bottleneck. Today Bosch is pioneering a new paradigm with "AI Spectrum Radar" (AISR), moving beyond single-purpose models to develop a versatile and large radar model. Our approach is built on three strategic pillars. First, we feed raw radar spectrum data directly into our models, preserving the full richness of the sensor's information. Second, we employ powerful Transformer-based architectures capable of learning a deep, contextual understanding of this data. Instead of training for one specific task, we use tasks like 3D occupancy as a dense, self-supervised pre-training objective. This teaches the model a "physics of radar" understanding that is broadly applicable. The power of this pre-trained foundation model is then demonstrated by its ability to solve downstream tasks, such as semantic segmentation, object detection, or BEV free-space estimation, with superior performance. We will showcase results from our live vehicle demonstration, supporting the immense potential of the approach. |
Handshake - The Human and AutomationVorsitz: Udo Steininger - TESACO GmbH |
Modeawareness Between L2-Hands-Off and L3 in a Field Operational TestDr. Bianca Biebl - BMW Group
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MiRoVA – Migration of Road Vehicle Automation From Theory to Application in the Automotive IndustryTassilo Ianniello - RWTH Aachen University
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Real Life - Automated Driving on the RoadVorsitz: Dr.-Ing. Christian Gold - BMW Group |
City, Countryside, Highway—Where Do Assisted Driving Functions Help in Cars?Dr.-Ing. Matthias Kühn - GDV e. V. Unfallforschung der Versicherer
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One Decade of BMW Field Operational TestDr. Mara Münder - BMW Group
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Wrap Up and FarewellDr.-Ing. Michael Fausten - Technology Innovation for Complex Systems | Engineering Transformation | AI-Enabled Physical Systems |