Computer simulations using virtual twins offer a time and cost-efficient way to improve testing and reduce R&D costs.
Generating Synthetic Data for AI Training
A virtual system created by NMY records and evaluates driving behavior, generates synthetic data for optimizing future driver assistance systems and interior solutions, and provides a glimpse into the autonomous driving of the future.
11.6 Bill. Avatar configurations
1 automatic batch process
4 years of optimization
Synthetic data generation01\
Data for AI Training
Optimal user guidance
The PC-based application is operated through an intuitive user interface and a wide range of functions, controls and menu options. This makes it easy to run through all possible scenarios during data generation.
AI thinks with you
Tools evaluate the data and provide valuable recommendations for optimizing the drive system and possibly discovering new, previously unseen features.
A configurator enables the creation of individual driver personas that can be customized down to the smallest detail.
In addition to the physical characteristics of the driver, lighting moods, weather conditions, and most importantly, the vehicle configuration can be designed.
A complex 3D rendering process, including video documentation, simulates the scenario and generates qualitative insights.
The repeated generation of situations yields synthetic data of high quality and quantity.
The application is a flagship project for digital transformation - and the response to the costly and resource-intensive analog processes of the past.
“By generating synthetic data in a realistic simulation, we can ensure high data quality and quantity. This is the basis for useful AI models that save time and money in product development.”