Lead Participant: Jaguar Land Rover Limited


"Autonomous vehicles are being developed with the promise of improving road traffic safety and convenience.

This project addresses a gap in the UK automotive supply chain, the algorithms used within the sensors add most of the value and this is an area where the UK can further develop ability and the UK should be able to generate significant revenues by exploiting this technology.

Autonomous functions that take control of the driving tasks off the human driver are heavily dependent on the system ability to perceive and understand the vehicle's surroundings through complex sensor systems. Most are actively emitting signals to use their reflections from the environment to understand the scene.

The sensor data-processing algorithms produce this understanding of the environment, enabling the autonomous function control system to adapt in response to prevailing conditions. The autonomous functions sensors will be the car's ""all-weather-eyes"" and their performance is fundamental to their reliability and safety, but there are insufficient comprehensive performance-verification methods and tools available.

The immediate future challenge comes from the co-existence of many active sensors in diverse traffic environments with high probability of their signals interfering with each other.

Autonomy function sensor performance verification is of unprecedented importance for reliable real-world autonomy as many vehicles with these sensors increasingly share the same road space.

This project will bring innovation through new sensors characterisation and new modelling methods building upon MoD-funded defence expertise, particularly for radar sensors. These models will enable studying autonomous functions performance through the simulation of challenging scenarios for the sensors in the real-world but challenging to replicate in a controlled real environment for assessment.

This consortium holds an unrivalled global-level strength and potential to describe and solve this challenge, by understanding of the complex interactions between environment, sensors and vehicles:

\*JLR --know-how of real-world automotive systems and their sensors requirements (the UK automotive manufacturing business with the largest investment in automotive R&D).

\*MIRA -developing the most comprehensive independent test services for the UK CAV ecosystem.

\*UoB -strong expertise in all aspects of radar systems, including hardware design, radar signature modelling, channel characterization and signal and image processing.

\*Igence -bespoke radar simulators for applications including airborne early warning, maritime surveillance, fighter aircraft and air traffic control. The project will directly support best-practice, guidelines, policy and regulation for the development and deployment of autonomous vehicles in the UK, effectively contributing to the transference of these technologies to the UK roads."

Lead Participant

Project Cost

Grant Offer

Jaguar Land Rover Limited, COVENTRY £900,184 £ 450,092


Horiba Mira Limited, Nuneaton £1,083,032 £ 541,516
University of Birmingham, United Kingdom £680,568 £ 680,568


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