Efficient Computer Vision ADAS Hardware for Connected and Autonomous Vechicles

Lead Participant: Myrtle Software Limited

Abstract

Bringing the next generation of Advanced Driver Assistance Systems (ADAS) hardware to automobiles is

complex, expensive, iterative and slow. Development and rollout in the marketplace is further slowed by the

high standards naturally required by the car industry. A major consequence of this situation is that advanced

computer vision algorithms, which are used in other industries for human safety, are not appearing as quickly

as they should within the increasingly connected cars on the roads today. This project is to explore the

feasibility of developing a new technology in realtime image processing to drastically reduce the iteration times

of producing ADAS hardware. The project will produce hardware versions of key algorithms using our software

and evaluate the efficiency of our new process. If successful this project would see the UK well-placed to be at

the forefront of owning the IP within all the chips in future car models and leading the way in making our roads

safer.

Lead Participant

Project Cost

Grant Offer

Myrtle Software Limited, Cambridge £210,211 £ 147,147

Publications

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