5D RAPID Project Secures GBP 2.5 Million for Advanced Radar Perception

5D RAPID Project Targets Advanced Radar Perception

On August 10, Oxford RF announced the GBP 2.5 million 5D RAPID Project, named after “5D Radar Perception for Intelligent Driving.” Funded through the UK Government's CAM Pathfinder Demonstrate programme, the initiative is focused on delivering advanced and scalable 5D radar perception for the automated driving market. The technology is intended to provide faster and more reliable understanding of moving objects while requiring fewer sensors than current systems. The programme brings together expertise from leading connected and automated mobility organisations in the United Kingdom, with Oxford RF coordinating a collaboration that includes IPG Automotive, Cranfield University, Coventry University, ECOSAR Tech, and Halo Drive.

Multi-Organisation Collaboration Supports Automated Mobility

The 5D RAPID initiative combines the capabilities of several organisations involved in connected and automated mobility, creating a collaborative development framework around advanced radar perception. Participants include IPG Automotive, Cranfield University, Coventry University, ECOSAR Tech, and Halo Drive, alongside Oxford RF. The project is designed to address the need for scalable perception systems capable of improving how automated driving platforms detect and interpret moving objects. By targeting greater perception capability with fewer sensors, the programme seeks to support more efficient sensing architectures for the evolving automated driving market while strengthening the UK's connected and automated mobility technology ecosystem.

Frequently Asked Questions

What is the 5D RAPID Project?
The 5D RAPID Project is a GBP 2.5 million initiative focused on advanced radar perception for intelligent and automated driving applications. Announced by Oxford RF on August 10, the programme is funded through the UK Government's CAM Pathfinder Demonstrate programme. It aims to develop scalable 5D radar perception that can provide faster and more reliable understanding of moving objects while using fewer sensors than current systems. The project brings together Oxford RF, IPG Automotive, Cranfield University, Coventry University, ECOSAR Tech, and Halo Drive to advance connected and automated mobility technologies.