Simulations require copious amounts of relevant scenarios to be able to successfully challenge the functionality of the Autonomous Driving System. However, this is largely cost-driven and involves high effort and time. At NavInfo Europe, we leverage our expertise in AI, Mapping, and Autonomous Driving to build up a closed-loop simulation testing solution and enable the fast and efficient creation of relevant, critical scenarios for Autonomous Driving simulation.
Our comprehensive simulation portfolio combines both Data and Knowledge driven approaches as a unique offering, which includes Scenario Extractor, Scenario Catalogue, Scenario Builder and Simulation RealMap. Each product allows our customers to meet their simulation needs and accomplish their verification and validation goals for ADS testing.
The Scenario Extractor is an engineering service to create concrete simulation scenarios from the customer vehicle data. Supported by our in-house AI technology, this service allows quick turnaround time through a fully automated pipeline to extract, identify and produce meaningful scenarios in an accurate way.
The Scenario Catalogue is an easily searchable cloud-based scenario database. It enables Autonomous Driving developers to quickly search, understand and access the scenarios, which speeds up the verification process and allows fast creation of simulation runs in an environment of their choice. The scenarios are published in OpenX formats to ensure the content is agnostic to be used.
The Scenario Builder functions as a platform solution for the parametric creation of scenarios for simulations following by an internal knowledge-based approach in the Autonomous Driving domain. This software allows you to design and customize scenarios, and automatically variate parameters that are tailored to your training needs.
The Simulation RealMap solution provides simulation maps of the real-world to help customers test and validate their autonomous driving functions. The real-world aspect of this service allows our customers to run tests under different geographical and environmental challenges.