rFpro offers wide support for HMD (head mounted display) devices. The more recent HMD models available now offer sufficient resolution and field of view combined with higher quality optics, and latency that is now low enough to be used for driving simulation.
HMDs and haptics provide a convenient user interface for the testing of HMI solutions: Evaluating the driving experience, the user interface and ensuring new ADAS and autonomous funcitonality works well with the driver and passengers. As you can see in the video above, the views in the rear view mirror and door mirrors are correct as the driver’s head moves.
HMDs provide a cost effective solution to adding large numbers of human test drivers into simulated autonomous driving experiments. rFpro experiments and tests can span multiple simulators. This means that a team of human test drivers can join an AV or ADAS simulation – a proven way to detect CAV failure modes. Humans are random and unpredictable and therefore valuable for both training and testing ADAS and AV systems. rFpro allows humans to join experiments without risk of injury or death.
Up to 50 simulations may participate in, and simultaneously share, the same virtual world. Your AI can be pushed to the limit, sharing roads packed with real human drivers, in a completely safe environment.
Simulating the real world, today, with human drivers sharing the virtual world with your AVs allows you to test years before your AVs actually meet humans in the real world.
For example, the following video, where some of the traffic on the highway is human, shows an AV trying to merge onto a highway. It demonstrates how important it is to disguise your AVs to look exactly the same as conventional vehicles.
Human drivers quickly learn that when a vehicle trying to merge is an AV you can just ignore it because its not going to risk forcing it’s way into your lane.
Learning this in simulation costs a fraction of a percent of the cost of building, maintaining and managing a fleet of real test vehicles. Simulation allows you to learn more, sooner and, critically, allows you to push your AI hard in complex scenarios where there is a risk to human road users.