Project Proposals

High-fidelity sensor simulation is becoming increasingly important for verifying and validating advanced driver assist and automated driving functions. In actual sensor-ECU combinations, communication is bidirectional which means that an ECU may request e.g. specific exposure settings from a camera. This project aims to identify use cases in sensor simulation where control data flows from the data consumer back to the signal generator. The focus will be on sensor types such as camera, radar, LiDAR, and potentially other technologies like ultrasound. Once these use cases are identified, the project group will work to either develop a concept or to enhance ASAM OSI, enabling it to support seamless, high-fidelity sensor simulation.




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ASAM SOVD has established itself as a powerful diagnostic API that can access vehicle data for both diagnostic and all other purposes. ASAM SOVD is particularly helpful for diagnosing and accessing vehicle data in the context of the software-defined vehicle (SDV). After the standard will be successfully transferred to ISO, we will continue the further development. The exact content of what is going to be performed will be discussed at the upcoming content definition workshop taking place on Oct 14 - 15, 2025 as hybrid meeting at Vector Informatik in Stuttgart.




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Trust in virtual homologation relies not only on the transparency of the simulation process, but also on the quality of the underlying models, frameworks, and related tools. While several initiatives and research projects, such as prostep IVIP, INTACS, SetLEVEL, EVIDENT, and HAIViSH, have advanced the discussion on credibility, there remains a critical gap: no standardized metrics exist to assess the quality of simulation frameworks and models, particularly in sensor simulation. The goal of this project is to start the discussion on a new standardized, machine-readable data format for storing and exchanging quality metrics for Simulation frameworks and models. The scope also includes defining an agreed, use-case–specific weighting of the respective metrics to emphasize features relevant to particular tasks.




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We are piloting a new, more agile approach to standards development for the Simulation domain. The proposed process aims to be more open, flexible, transparent and collaborative. The pilot will run until Dec 2025. A subsequent evaluation will determine whether this approach will be adopted for all future standard developments at ASAM.




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This ASAM project aims to standardize key aspects of Vehicle Occupant Monitoring Systems (VOMS) through two deliverables: a platform-independent API for seamless integration of VOMS into vehicle systems, and a standardized data model (VOMS-QA) for the testing and validation ecosystem around VOMS. The future standards will support interoperability, enable efficient toolchain integration, and foster innovation in safety-critical applications. Alignment with existing ASAM standards (e.g. ASAM OpenX standards) will be explored during the project.

Participating Companies
Ansys, Inc., ANYVERSE SL, Robert Bosch GmbH, Deepen AI, Deutsches Zentrum für Luft- und Raumfahrt e.V. DLR, Driving Simulation Association, ITK Engineering GmbH, KPIT Technologies GmbH, Luxoft GmbH, MORAI Inc., Politecnico di Torino, roboGaze Kft., Vicomtech, Virtual Vehicle - Das virtuelle Fahrzeug Forschungsgesellschaft mbH, WMG University of Warwick


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After the release of the ASAM OpenTestSpecification concept paper, ASAM is now ready to initiate a follow-up project. This project aims to extend three major ASAM standards, ASAM ODS, ASAM OTX Extensions, and ASAM XIL, with the goal to align their development with the requirements outlined in the concept paper. Additionally, a new overarching Standard "ASAM TestSpecification" may be developed, depending on the further development of some of the concepts.

Participating Companies
51Sim Computer Systems Co.,Ltd., Akkodis Germany Consulting GmbH, Ansys, Inc., AVL LIST GMBH, BMW Group, Desay SV Automotive Co., Ltd., dSPACE GmbH, emotive GmbH & Co. KG, ETAS GmbH, Ford Motor Company, Hexagon Manufacturing Intelligence, HighQSoft GmbH, Astemo Ltd., imbus AG, Jaguar Land Rover, Karakun AG, KENOTOM Private Company, KPIT Technologies GmbH, Peak Solution GmbH, RA Consulting GmbH, Robert Bosch GmbH, Schaeffler/Vitesco Technologies GmbH, Technica Engineering GmbH, tracetronic GmbH, Vayavya Labs Pvt. Ltd., Volkswagen AG


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