Omar Elzeiny

As Mechatronics engineer, I Started at dSPACE in early 2017 and had since then a variety of positions as a field application engineer, business developer and a product Manger. Having this variety of roles at dSPACE allowed me to have the proper understanding of both the commercial and technical value for the end-to-end solutions for data driven development which includes Data logging, data Management, data enrichment and data replay.

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Presentation

Data management and the homologation challenge

To introduce automated driving systems (ADS) to market, OEMs must demonstrate ethically acceptable safety levels, which requires achieving a positive risk balance amid numerous real-world risk factors. Real-world data insights must be complemented with model-based and scenario-based testing methodologies. In this talk, we will explore leveraging AI for identifying critical data sequences and using advanced technologies like GenAI for automated scenario generation. Additionally, we will outline innovative solutions in smart fleet management to address data coverage gaps for ADS development and validation. This holistic approach aims to accelerate development cycles by optimizing data acquisition and enhancing safety validation processes.