Digital Models


rFpro has created an ever-growing library of highly accurate digital models which that consists of more than 100 locations of other public road routes, proving grounds and test tracks. There are a large number of private models too that have been commissioned by our customers of their own proving grounds and testing locations. rFpro offers the world’s largest library of off-the-shelf digital models of proving grounds, public roads, test tracks and race circuits for F1, NASCAR, WEC, IMSA, Indy, Formula E and Super-GT.

They are modelled using survey-grade LiDAR scan data to create a vehicle dynamics grade road surface, which is accurate to within 1mm in the vertical axis. This is key to accurately simulating the effects of every bump, drain cover and expansion joint at a location. The starting point for any new model is a contiguous LiDAR survey with geo-referenced, spherical photography. Our road building process then creates the road surfaces and reference material used for the scenery in the completed 3D digital models.




Vehicle Dynamics Development

For drivers testing aspects of vehicle dynamics, these models come with accurately modelled digital road surfaces. Accurate, high-frequency LiDAR is used to capture the road and kerb detail that is critical for vehicle dynamics applications. Longer range time-of-flight LiDAR is used to capture the road side features and scenery. With rFpro’s Terrain Server, every bump, ripple and discontinuity will find its way through your tyre model into your vehicle. And vehicle models can consume this very detailed road surface data in real-time, while an offline interface also exists for ride and durability studies that have no real-time requirement.

ADAS and Autonomous Vehicle Development

For engineers training and testing their ADAS and deep learning autonomous driver models, our road models offer a very high level of correlation between real and virtual worlds, ensuring that algorithms trained in our environments perform well in the real world. The environments within our models are not only geometrically precise but functionally accurate too, with each of the thousands of road signs, markings, and roadside objects being individually classified. This is critical for the development of many ADAS and autonomous systems that rely on panoptic segmentation for their training data sets. The models also enable users to add intelligent and scripted traffic to create an almost infinite number of test scenarios in this model. The types of vehicles, their speeds, colour and density of traffic can be varied and more.

The rFpro simulation software also allows a large number of humans to drive within the digital model at the same time, enabling the most complex edge case scenarios to be created and recorded. This offers a cost and time-effective way of creating large quantities of usable training data to improve a vehicle’s artificial intelligence.

To learn more about how our simulation environment is used by the automotive industry for the development and testing of autonomous vehicles, ADAS and vehicle dynamics, visit our Applications section.