Modelling, Simulation and Testing of Automotive Perception Sensors
Sim4CAMSens was a series of CCAV funded projects that worked on methods to quantify and model camera, radar and lidar sensor performance under all conditions for ADAS, Autonomous Vehicles and In-cabin simulations.
Project Partners
AESIN is an outstanding member-based community enabling the next generation of UK-centric automotive electronics & software systems and supply chains. Leading thought and impact for ingenious, sustainable, efficient, safe, and resilient mobility through the innovative application of electronics & software systems.
Compound Semiconductor Applications (CSA) Catapult was established in 2018 by Innovate UK to help the UK become a global leader in compound semiconductors. CSA Catapult is the UK’s authority on compound semiconductor applications and commercialisation.
Claytex is a consultancy, developer and distributor of modelling and simulation solutions for systems engineering, focused on simulating the dynamics of how systems behave and interact. Claytex’s vehicle simulation solution for ADAS and Autonomous Vehicles provides sensor realistic simulation using the rFpro simulation environment.
The National Physical Laboratory (NPL) is a world-leading centre of excellence that provides cutting-edge measurement science, engineering and technology to underpin prosperity and quality of life in the UK.
Oxford RF provides the world’s first solid-state 360 and 270 ADAS and ADS sensors (enabling full 360-degree or 270-degree sensing without any moving parts). The patented sensor technology has lower size, weight, cost and power consumption compared with existing solutions in the market.
rFpro AV elevate is an engineering-grade simulation environment for the ADAS and Autonomous vehicle simulation. It’s used for the development and testing of autonomous vehicles, ADAS, vehicle dynamics and human factor studies – essentially anything that involves driving a vehicle.
Syselek develops innovative technology and toolchain solutions using automation for high integrity systems. Our solutions are built upon our deep technical expertise, research, engineering, and innovative technologies.
Professor Valentina Donzella is Professor in Sensors and Perception for Intelligent Systems and head of the SPRING group (Sensing and PeRception for INtelliGent Systems) in the School of Engineering and Materials Science. During the project, Professor Donzella moved her research group from WMG, University of Warwick, to QMUL, where the group’s work on quantifying noise factors and validating sensor models continued.
Scope of Work
The Sim4CAMSens project was set up to make a step forward in perception sensor modelling fidelity for autonomous vehicle and ADAS simulation through combined test data collection, analysis and model development activities.
The project carried out an extensive test program to collect data on the performance of camera, radar and LiDAR under a wide range of conditions including lab-based testing, field work and automotive proving ground tests. The tests were designed to explore and identify the noise factors that affected sensor performance.
The modelling and simulation activities enhanced the sensor models for camera, LiDAR and radar and the virtual worlds that they see.
Material property studies were carried out to populate new databases within the simulation tools, so that every object had the appropriate material properties for the wavelength that the sensor was working at.
The sensor models focused on modelling the physics of how light and em-waves propagated through the environment and returned to the detectors.
The validation process for sensor models was developed with support for safety assurance processes in mind. This work explored the topic of simulation tool credibility and produced a set of guidelines for sensor model validation.
The Sim4CAMSens2 project built on the work in the original project and extended the focus from exterior to also include interior-facing sensor systems, addressing the growing importance of in-cabin monitoring for safety and autonomy.
The project developed more efficient sensor characterisation methods, examined how perception systems performed in degraded conditions and continued the work on sensor model and simulation validation, including developing the link to safety assurance processes.
Project Outputs
AV elevate is an award-winning, fully integrated simulation solution for developing and testing ADAS and autonomous vehicle systems. Building on the sensor modelling and validation work carried out during Sim4CAMSens, it combines rFpro’s ray-traced simulation environment with high-fidelity camera, radar and LiDAR sensor models to enable closed-loop perception testing and generate engineering-grade synthetic training data, reducing reliance on real-world testing.
The CAV Catalogue, developed by Syselek, collects publicly available information about Level 4 Automated Vehicles and their perception system sensors. This is a unique, comprehensive, and freely accessible online resource covering more than 150 models from AV developers worldwide, past and present.
Syselek developed a new Perception System Requirements Cascade Methodology using a V-Model approach to determine traceable functional requirements for an Automated Vehicle’s perception system in any intended application. The methodology also informs the necessary fidelity of simulation-based evidence for safety assurance.
UNECE regulations define the need to demonstrate the credibility of the simulation toolchains used for safety assurance evidence. Syselek developed a new procedure and accompanying guidance to enable Automated Vehicle manufacturers to systematically prepare their evidence for safety assurance.
The H360 Series is the world’s first solid-state 360° radar sensor, delivering full horizontal coverage without any rotating antennas or moving parts. Removing mechanical components reduces complexity, cost and the risk of failure, while the sensor performs reliably in all weather and visibility conditions. With a sensing range of up to 130 metres and a 4D point cloud output, it suits demanding automotive, robotics and industrial applications. Contact Oxford RF for more information.
The A270 Series is a solid-state 270° automotive radar developed for 5D/6D perception in future ADAS and autonomous driving systems. Its wide, overlapping field of view allows data from multiple sensors to be combined for higher-resolution sensing and built-in redundancy, enabling a centralised sensing architecture with as few as four sensors per vehicle. With a 200 metre range and resilience to interference, jamming and spoofing, it offers cost-effective coverage from entry-level to luxury vehicles. Contact Oxford RF for more information.
Project Funding
Sim4CAMSens was part of CCAV’s Commercialising CAM Supply Chain Competition (CCAMSC) and ran from 2023 to 2025.
The Commercialising CAM programme is funded by the Centre for Connected and Automated Vehicles, a joint unit between the Department for Business and Trade (DBT) and the Department for Transport (DfT) and delivered in partnership with Innovate UK and Zenzic.
The CCAM Supply Chain competition was launched in October 2022 to support the delivery of early commercialisable Connected and Automated Mobility technologies, products and services and is part of the Government’s vision for self-driving vehicles. Connected and automated mobility 2025: realising the benefits of self-driving vehicles.
SIM4CAMSens 2 was funded through the £150million CAM Pathfinder programme announced in the UK Government’s Advanced Manufacturing Sector Plan. The programme was funded by the Centre for Connected and Autonomous Vehicles (CCAV), delivered in partnership with Innovate UK and Zenzic.
The CAM Pathfinder 1 – Enhancements competition was launched in December 2024 to target early commercial self-driving vehicle opportunities and support the UK supply chain to grow and fill technology gaps necessary for their deployment and is part of the Government’s vision for self-driving vehicles. Connected and automated mobility 2025: realising the benefits of self-driving vehicles.
Get Involved
The project established an advisory board with members covering the whole supply chain. The board included chip designers, sensor developers, ADS developers, OEMs and test authorities who helped steer the project and gained early access to its results.
For information about the project and its outputs, please contact us via the form or contact the partners directly using the links above.