Skip to main content

Zenuity and CERN to develop AV machine learning

Zenuity has joined forces with CERN, the European Organisation for Nuclear Research, to develop fast machine learning for autonomous vehicles (AVs). Zenuity - an autonomous driving software company - is hoping the collaboration will aid the development of AVs that can make decisions and predictions more quickly, thereby avoiding accidents. The partners will also aim to reduce the runtime and memory footprint of deep learning algorithms while minimising energy consumption and cost. They will use CERN’s
September 5, 2019 Read time: 1 min

Zenuity has joined forces with CERN, the European Organisation for Nuclear Research, to develop fast machine learning for autonomous vehicles (AVs).

Zenuity - an autonomous driving software company - is hoping the collaboration will aid the development of AVs that can make decisions and predictions more quickly, thereby avoiding accidents.

The partners will also aim to reduce the runtime and memory footprint of deep learning algorithms while minimising energy consumption and cost.

They will use CERN’s Field-Programmable Gate Arrays, a hardware solution that is expected to execute decision-making algorithms in micro-seconds for machine learning applications. 

Related Content

  • November 11, 2016
    Continental and Oxford University jointly researching artificial intelligence
    International technology company Continental and the Department of Engineering Science at the University of Oxford are now conducting joint research in the field of artificial intelligence in a partnership which will focus on the possible uses and development of artificial intelligence algorithms, which have the potential to further enhance future mobility applications. These deep-learning algorithms have the potential to deliver future visual object detection and human–machine dialogue.
  • January 15, 2019
    Aimsun enters partnership to develop tool for managing mixed-autonomy traffic
    Aimsun has partnered with UC Berkeley’s Institute of Transportation Studies to develop Flow, a tool for managing large-scale traffic systems where human-driven and autonomous vehicles (AVs) operate together. Flow offers a suite of pre-built traffic scenarios and is now integrated with Aimsun Next mobility modelling software. The open source architecture knits together microsimulation tools with deep reinforcement learning libraries in the cloud. Launched last September, Flow allows users to build and
  • May 16, 2022
    Commsignia stops AVs behaving badly
    Cybersecurity concerns surrounding autonomous vehicles create uncertainty but Commsignia has set out to win trust by combating ‘misbehaviour’ attacks, finds Ben Spencer
  • October 26, 2017
    USDoT looks at the costs and potential benefits of connected vehicles
    David Crawford looks at latest lessons learned from the trials of connected vehicles in the US. The progress of connected vehicle (CV) technologies takes centre stage among the hot topics highlighted in the September 2017 edition – the first since 2014 – of the ‘ITS Benefits, Costs and Lessons Learned’ survey from the US ITS Joint Program Office (JPO). The organisation is an arm of the US Department of Transportation (USDoT).