Krumm cites the benefits of AURELION’s start-to-finish approach. “We are providing an end-to-end solution where AURELION plays a major role in giving the customer the good feeling and knowledge that he has the best sensor models in terms of radar, LIDAR, camera, and ultrasonic under one hood,” he says. “So, you can test this AV development process from the beginning, with the virtual simulation, up to the hardware where the real code is going into a car and it can be driven on a road prototypically.”Currently dSPACE is updating AURELION to Unreal Engine 5 and also implementing new tools to support customers, including a planned dSPACE plugin for Unreal Engine that will enable their customers to import formats like OpenDRIVE—the standard for describing road networks—then build environments in the Unreal Editor, and load them into AURELION.
“I personally think we’ve found the best solution for the market with Unreal Engine,” says Seiger. “If we had stayed with OpenSceneGraph, for example, instead of Unreal Engine, we would still be working on lighting issues and other things like that forever, and there wouldn’t be an AURELION today.”
In the decades that come, as autonomous vehicles become ubiquitous on roads all over the world, dSPACE plans to stay on the front line of AV simulated training. Learn more about providing sensor-realistic simulation and top-grade visualization for developing and validating driving functions by visiting the Unreal Engine Simulation page.
Source: Unreal Engine Blog