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Industry Summary Articles

Monday, September 08, 2025

Claytex Leads Collaborative Development of Simulation for Autonomous Vehicles

TECHNIA, a leading provider of virtual twin solutions and digital engineering, announces that its subsidiary Claytex will lead the Sim4CAMSens2 collaborative project, advancing simulation technology for autonomous vehicle (AV) safety assurance and industry-leading sensor modelling and validation.

The Sim4CAMSens2 project represents a major step forward in AV development, focusing on validated simulation platforms that close the critical gap between physical and virtual testing environments. As project leader, Claytex will coordinate the consortium’s work to deliver comprehensive simulation solutions for AV safety case evaluation, advanced sensor noise categorisation, and accelerated validation methodologies.

At TECHNIA, we are committed to driving innovation that shapes the future of safe mobility. By supporting Claytex in leading this important collaboration, we’re ensuring that the industry gains access to world-class simulation capabilities and trusted tools for the next generation of autonomous vehicles.”
Magnus Falkman, CEO | TECHNIA

Building on Previous Success
This initiative builds on the achievements of the first Sim4CAMSens project, which established virtual environments and sensor modelling capabilities through extensive winter testing. The new phase will focus on two primary objectives: developing efficient, cost-effective validated sensor models and creating high-fidelity in-cabin simulations that match the realism of exterior environments.

At TECHNIA UK and Claytex, we’re proud to lead the Sim4CAMSens2 project, working with some of the best minds in the field to push the boundaries of AV simulation. Our mission is to make simulation outputs indistinguishable from real-world data, giving the automotive industry the confidence and validated tools it needs for safety-critical development.” Michael Hurst, Managing Director | TECHNIA UK and Claytex

A Strong Consortium of Industry Leaders | The Sim4CAMSens2consortium brings together leading organisations, each contributing specialist expertise across physical and virtual domains:

  • rFpro | Simulation and virtual environments
  • National Physics Laboratory (NPL)| Metrology and measurement standards
  • Oxford RF | RF technology and validation
  • Queen Mary University of London| Academic research and modelling
  • Syslek | Systems engineering and integration
  • Catapult CSA | Compound semiconductor applications
  • AESIN | UK automotive electronics innovation network

This collective expertise ensures a robust, comprehensive approach to AV simulation for safety assurance.

Claytex’s primary role is to define critical standards for Lidar and Radar sensor simulation, drawing on extensive data from winter and laboratory testing to prioritise and replicate the key factors affecting sensor performance. A secondary focus is the development of advanced in-cabin simulation, ensuring that interior environments achieve the same fidelity as external conditions.

Project Deliverables | The consortium will focus on:

  • Development and validation of simulation platforms for AV safety case evaluation.
  • Comprehensive categorisation and simulation of sensor noise effects.
  • Accelerated testing methods to bridge the gap between physical and simulated sensor models.
  • Evaluation procedures to support AV safety approval authorities in AV safety case assessment.
  • Integration of in-cabin simulations, including IR and Radar sensor modelling.

All deliverables will be directly integrated into AV elevate, enhancing accessibility to the highest-fidelity safety case testing.

The combination of advanced sensor modelling and validated simulation environments represents a vital step toward safer autonomous vehicles. This collaboration ensures the industry has the tools it needs to confidently transition from virtual validation to real-world deployment.” David Briant, AV Team Leader | Claytex

To view the original press release, please click here.

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