Simulator supports multiple robotaxis

April 20, 2021 // By Nick Flaherty
Simulator supports multiple autonomous vehicles
Szabolcs Jánky at AImotive talks to Nick Flaherty about how the aiSim 3.0 simulator supports multiple independent autonomous vehicles in a virtual environment

The latest simulator technology from Budapest-based AImotive supports multi-node, multi-client operation to allow multiple autonomous vehicle designs to be simulated in the same virtual environment, says Szabolcs Jánky, aiSim Product Manager at AImotive.

Currently only one vehicle design can be validated in a simulator, with other vehicle represented by models. One vehicle uses one GPU for a vehicle with a small sensor, or 6 GPUs to run a detailed simulation of a robotaxi with multiple sensors, and aiSim3.0 allows up to four, 10 GPU racks to be combined. The software can also  be used in cloud systems and is built on open APIs such as the Vulkan ray tracing API from Khronos to allow portability between GPUs

“We don’t use proprietary libraries from hardware vendors for ray tracing or physics models, and with the recent support for ray tracing from Khronos we were able to switch to open APIs with Nvidia, AMD and Intel,” said Jánky.

“In the cloud we don’t have a software limit, the limit is the architecture of the cloud, the connection between the nodes,” he said.

“When it comes to server infrastructure there is a huge difference between AMD nodes and Nvidia nodes so we want to give the option to switch as necessary. In automotive everything is about standards and customers want to mitigate the risk of being locked in – this is the case in hardware but it is starting to be the case with the software infrastructure as well,” he said.

aiSim3.0 is a ISO26262 certified simulator for the development and validation of ADAS and AD systems. AImotive built its own engine to provide accurate physics for the sensors, particularly issues such as fog or rain, rather than using the Unity or Unreal gaming engines.

The focus is on testing sensors, including camera, lidar and radar fusion in a wide range of scenarios. Using simulation allows edge and corner cases to be validated, he says.

“Unreal and Unity have their limitations

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