Make it British: Supporting sovereign UK supply chain for connected and automated mobility
£18.5 million is being made available to UK companies in government funding to strengthen the capabilities of the UK’s connected and automated mobility supply chain.
- £18.5 million is being made available to UK companies in government funding to strengthen the capabilities of the UK’s connected and automated mobility supply chain
- 13 projects will improve the safety and security of self-driving vehicles, by filling specific technology gaps, improving performance, reliability and scale-up opportunities in the UK and globally
- the grants, part of the Centre for Connected and Autonomous Vehicles Connected and Automated Mobility programme, will complement £81 million investment for CAM technology
The grants, as part of the Centre for Connected and Autonomous Vehicles (CCAV) Commercialising Connected and Automated Mobility: Supply Chain competition, will help 43 British companies across 13 projects seize early opportunities to develop self-driving technologies, products and service ready for the connected and automated mobility market.
In August 2022, the Government announced its approach to supporting the safe deployment of self-driving vehicles to deliver societal and economic benefits. It is the Government’s vision that the UK will start seeing the deployments of commercially operating self-driving vehicles, improving the ways in which people and goods are moved across the nation. To turn this vision into reality, CCAV launched the Commercialising Connected and Automated Mobility (CCAM) programme to target early commercial self-driving vehicle opportunities and support the UK supply chain to grow and fill technology gaps necessary for their deployment.
On 1 February 2023, the Government announced the winners of its deployments competition, where 7 successful projects from around the UK form the most advanced set of commercial, self-driving passenger and freight operations anywhere in the world. Projects are now underway in Belfast, Edinburgh, Sunderland, Strategic Road Network, Coventry and Cambridge.
With a total funding of £28.5 million in joint Government and industry support, 13 new supply chain projects will complement the deployment projects and will play a pivotal role in advancing the self-driving revolution by reinforcing the UK’s position at the forefront of connected and automated mobility technologies.
These projects will be delivered in partnership with CCAV’s delivery partners, Zenzic and Innovate UK to bring together government and industry to support the development of sovereign capabilities within the UK CAM supply chain. The selected projects will address critical technology gaps, enhance safety and security, improve performance and reliability, and create scalable opportunities both domestically and globally.
Combined, the deployments and the supply chain projects will help increase safety and efficiency of operations – a great result for our communities and our economy as we gradually roll these services and solutions out nationally and export them globally.
The joint government and industry funding winners are:
AIM-DBW
The project aims to deliver a universal and affordable drive-by-wire system that replaces traditional mechanical linkages with electronic ones. This system enables automation of the throttle, steering, braking, gears, and ancillary systems of a vehicle.
- Partners: AIM TECHNOLOGIES (Lead) and TRL
- Grant funding: £400,000
Autonomous Cargo
This project focuses on creating an autonomous dolly for airside cargo movements. Building on previous experience with smaller baggage dollies, the project will develop a unique autonomous airside 7.5t cargo dolly. Additionally, a simulation tool will be developed to quantify the benefits of CAM for air cargo operations, providing operators with insights into optimal CAM vehicle types or required infrastructure modifications.
- Partners: AURRIGO (Lead) and UPS
- Grant funding: £480,000
CERTUS
The verification and validation of ADS presents unique challenges. CERTUS provides a toolset that helps to efficiently identify, define and execute the test requirements for an ADS. It addresses three key questions: what to test, how to test, and when to stop testing. The project partners will collaborate to develop and demonstrate effective testing methodologies.
- Partners: HORIBA MIRA (Lead), COVENTRY UNIVERSITY, CONNECTED PLACES CATAPULT, POLESTAR AUTOMOTIVE UK, IPG AUTOMOTIVE UK
- Grant funding: £1.5 million
DeepSafe
DeepSafe aims to support the verification and validation (V&V) of automated driving systems (ADS) through the development and deployment of industry-critical data and a next-generation simulation toolchain. By combining high acuity data recorded with a new high-speed test methodology operating in real world environments, and high-volume simulation mediated by world-leading raytraced simulation, the project will address the “reality gap” on the most critical scenarios to train ADS against high-impact collisions, emergencies, and the whole landscape of edge cases. Adding a novel AI-based software for backtracking failure modes to their source, the project hopes to finally unblock the way to safe and economical AV deployments.
- Partners: DRISK.AI (Lead), IMPERIAL COLLEGE LONDON, CLAYTEX SERVICES, DG CITIES, RFPRO
- Grant funding: £2 million
DriveSafeAI
DriveSafeAI will develop a safety assurance framework for the safe deployment of AI in self-driving technology across all driving domains. Bringing together Wayve’s next-generation end-to-end AI approach to self-driving, with WMG’s expertise on the safety of automated systems, DriveSafeAI will deliver a set of safety methods, tools and datasets that will support the whole self-driving industry.
- Partners: WAYVE TECHNOLOGIES (Lead) and UNIVERSITY OF WARWICK
- Grant funding: £1.9 million
DRIVEN BY SOUND
DRIVEN BY SOUND is a collaborative initiative to create an affordable, robust navigation system for automated vehicles, with a particular emphasis on adverse weather handling. This system features a high-performance computer supporting all levels of automated and autonomous driving. It incorporates cutting-edge 3-D ultrasound sensors for safety and redundancy, ruggedisation for durability, and robust cybersecurity measures.
- Partners: CALYO (Lead) and BARO VEHICLES
- Grant funding: £910,000
evolvAD
Building upon previous Nissan project experience, evolvAD aims to develop an AV capable of safely driving in residential, urban, and rural environments. Project partners will focus on HD map generation and validation, alignment with multiple complex operational design domains (ODDs) and improving interactions in complex urban environments with vulnerable road users.
- Partners: NISSAN MOTOR MANUFACTURING UK (Lead), TRL, HUMANISING AUTONOMY, CONNECTED PLACES CATAPULT, SBD AUTOMOTIVE
- Grant funding: £2.3 million
High-Performance Imaging Radar (HPIR)
This project aims to develop a high-performance imaging radar product specifically designed for AVs. By addressing a gap in the CAM Supply Chain UK, it will enable more robust, cost-effective systems that can operate in a wider range of weather conditions while reducing reliance on lidar.
- Partners: APTCORE (Lead), GARFIELD MICROELECTRONICS, PLEXTEK SERVICES, CAMBRIDGE SENSORIIS
- Grant funding: £1.8 million
Photonic Inertial Sensors for Automotive (PISA)
This project aims to develop advanced position and navigation sensors that work reliably in various environments. By leveraging Micro Electromechanical Systems (MEMS), Photonic Integrated Circuits (PICs), and low-cost laser/detectors, the project will improve the performance, resilience, and safety of autonomous vehicles (AVs) by reducing reliance on vulnerable external signals.
- Partners: ZERO POINT MOTION (Lead), WAE TECHNOLOGIES, UNIVERSITY OF THE WEST OF ENGLAND, ROYAL INSTITUTE OF NAVIGATION
- Grant funding: £1.4 million
Sim4CAMSens
Sim4CAMSens aims to enable accurate representation of ADS sensors in simulation. It will develop a sensor evaluation framework that spans modeling, simulation, and physical testing. This project will involve the creation of new sensor models, improved noise models, new material models, and new test methods to allow ADS and sensor developers to accelerate their development.
- Partners: CLAYTEX SERVICES (Lead), UNIVERSITY OF WARWICK, NATIONAL PHYSICAL LABORATORY, SYSELEK (UK), COMPOUND SEMICONDUCTOR APPLICATIONS CATAPULT, RFPRO, OXFORD RF SOLUTIONS, TECHWORKSHUB
- Grant funding: £2 million
StreetCAV
StreetCAV will create a ‘plug-and-play’ roadside connectivity solution enabling self-driving shuttles, robotic and drone-based services to operate safely and securely, maintaining connections wherever they go. With world-class experts and UK-based partners, we will deploy StreetCAV and a new self-driving shuttle service into Milton Keynes, as a blueprint for UK-wide deployment.
- Partners: SMART CITY CONSULTANCY (Lead), DELL CORPORATION, MILTON KEYNES BOROUGH COUNCIL, OHMIO UK
- Grant funding: £1.8 million
Systems for Autonomy in Fail Operational Environments (SAFE)
The SAFE project will develop a fully redundant, fail-operational Drive-by-Wire technology platform to enable safe driver-out, on-road autonomous vehicle capability. By integrating purpose-built sub-systems, the project will create an automated vehicle capable of achieving SAE Level 4 autonomy. These safety-critical vehicle systems ensure lateral and longitudinal control, even in the event of a single-point fault or failure.
- Partners: STREETDRONE (Lead), ALCON COMPONENTS, UNIVERSITY OF SURREY, CHASSIS AUTONOMY
- Grant funding: £1.2 million
Torque Overlay Automated Steering Technology (TOAST)
The TOAST project focuses on the development of a modular dual redundant steer-by-wire system for heavily automated and electric vehicles. This project fills a gap in the UK supply chain, supporting ADS development in the UK and globally, as there is currently no UK-based Tier 1 supplier showing interest in supporting low to medium volume vehicle manufacturers.
- Partners: TITAN MOTORSPORT & AUTOMOTIVE ENGINEERING (Lead), ALEXANDER DENNIS, TRL
- Grant funding: £760,000