Synchronizing and processing high-bandwidth data in ADAS and automated driving development applications
Nicolas du Lac, CEO, INTEMPORA | LinkedIn
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Modern methods for developing, testing and validating complex software functions for advanced driver assistance systems (ADAS) and autonomous driving (AD), such as perception, positioning, and decision-making, require vast amounts of sensor data to be gathered. Once the data is collected, it must be post-processed for AI algorithm training and validation so that functions can be executed in real-time in the field.
In this free, 60-minute webinar, Intempora CEO Nicolas du Lac discusses how RTMaps software, and potentially other technologies from the dSPACE data-driven development toolchain, can help engineers across the various stages of the development and testing cycles – from data collection to “as-fast-as-possible” data replay, including real-time execution in vehicles.
Key topics and takeaways:
- Easy-to-use, modular and powerful software framework for speeding up complex AD software development and testing tasks
- Guidelines to optimize your IT infrastructure for training, testing and validation of algorithms against large amounts of data
- End-to-end toolchain for data-driven development