In SYNTRA, NovelSense is developing a Software-as-a-Service (SaaS) solution to generate synthetic traffic datasets to be used in the training, testing and benchmarking of AI-based traffic monitoring systems.
The goal is to make high-quality traffic data available to enable safe autonomous driving. Real data collection is costly and has privacy issues, while existing datasets are limited, unrealistic and often restricted to academic use.
Through the SYNTRA project, NovelSense will improve their existing product and extend their portfolio by offering realistic traffic datasets optimized for the custom needs of developers. SYNTRA employs EUH4D Services to support the technical realization, the business strategies and stakeholders requirements.
The main objectives of the SYNTRA experiment are:
- the creation of the SYNTRA Webapp through which customers can acquire customized synthetic traffic datasets for commercial use
- the improvement of ABAKUS.AI traffic recognition model through the generated synthetic data
- The development of a software as a service solution to provide customized traffic data based on simulation and augmentation
- Creation of a free commercially usable dataset for AI-based traffic system development
- Employ synthetic traffic data to improve the ABAKUS.AI product
The project will simplify access to high-quality traffic data for training, testing and benchmarking AI models. This helps AI traffic engineers to develop more robust and better characterized models. Municipalities and their citizens benefit from more cost-efficient and accurate real-time traffic monitoring to improve traffic planning and control, or through environment friendly shuttle services which recognize vulnerable traffic participants in complex scenarios.
Main expected results / Key Exploitable Results (KERs) SYNTRA generates the following KERs which are directly linked to NovelSense' core business:
- Improves the ABAKUS.AI traffic model through synthetic data
- Synthetic data SaaS offering based on refined data driven business strategy
- Aid the development of automatic driving by improving infrastructure based traffic monitoring
- Extended consulting for the mobility space due to increased tooling and expertise
- Generation of synthetic traffic data
- Implementation of augmentation methods
- Validation of synthetic data using ABAKUS.AI model