Digital models of Millbrook to help advance AV system development

Millbrook has invested in the development of a digital model of the proving ground. Created by UK software company rFpro, the model will enable vehicle manufacturers to accelerate the development of ADAS and autonomous systems virtually.

“The software for ADAS and autonomous systems need to be trained and tested on a digital copy of the proving ground before it is ready for real-world testing,” explained Chris Hoyle, technical director, rFpro. “By investing in a digital model, Millbrook’s proving ground becomes a simulated part of its customers’ Continuous Integration software development toolchain. This significantly reduces the development and validation time, and therefore cost, of such systems.”


The process used by rFpro adopts phase-based laser scanning survey data to create models with an accuracy of around 1mm in z (height) and in x and y (position). The Millbrook model contains over 50km of various types of road, including ADAS and autonomous facilities, wet and dry handling, ride and durability routes.

The virtual environment can be populated by ego vehicles (the customer’s vehicles) as well as by semi-intelligent Swarm traffic and programmed traffic. Vehicular and pedestrian traffic can share the road network correctly with perfectly synchronized traffic and pedestrian signals, following the rules of the road, while also allowing ad-hoc behavior, such as pedestrians stepping into the road, to provoke an emergency. This enables digital experiments to precisely mirror the real-world tests conducted on the physical proving ground at Millbrook.

Human test drivers can interact with this virtual world in full-scale driving simulators, or at desktop workstations with basic steering and pedal controls. This enables the testing of cars with ADAS systems, for individuals to experience being a passenger in a car under the control of a fully autonomous system, and enables driving in the virtual world to either subjectively assess the behavior of autonomous vehicles, or to provoke emergency scenarios and evaluate the response.

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