CERN developing faster machine learning for AVs


Swedish autonomous driving software developer Zenuity has become the first automotive company to team up with CERN, the European Organization for Nuclear Research, in the development of fast machine learning for self-driving cars.

A fundamental challenge in the development of autonomous vehicles (AV) is the interpretation of the huge quantities of data generated by normal driving conditions, such as identifying pedestrians and vehicles with the sensors on the car, including cameras, lidar and radars. Addressing these issues is crucial for the development of safe AVs and is a key part of Zenuity’s long-term ambition to speed up the development of vehicles that will completely eliminate collisions and associated injuries and fatalities. Zenuity hopes that this collaboration with CERN will ultimately help it develop AV that can reach decisions and make predictions more quickly, thus avoiding accidents.

One of the main quests at CERN is to study the standard model of particle physics by collecting large quantities of data originating from particle collisions produced by CERN’s Large Hadron Collider (LHC) located at its laboratory on the Swiss-French border. Both particle physics and autonomous vehicles require fast decisions to be made. CERN has approached this challenge by using Field-Programmable Gate Arrays (FPGAs), a hardware solution that can execute complex decision-taking algorithms in micro-seconds. The synergy between Zenuity and CERN aims to use FPGAs for fast Machine Learning applications, to be used in the AV industry and in particle physics experiments.

The research to be conducted under the collaboration concerns so-called ‘deep learning’, which is a class of machine learning algorithms. In recent years such algorithms, commonly referred to as artificial intelligence (AI), have been applied to a multitude of fields with great success, even exceeding human performance on certain tasks. Zenuity hopes that its collaboration with CERN will push the frontiers of this technology by reducing the runtime and memory footprint of the relevant deep learning algorithms without reducing accuracy, while simultaneously minimizing energy consumption and cost. The collaboration forms part of CERN’s knowledge transfer activities to engage with experts in technology and industry, in order to maximize the positive contribution of CERN technologies on society.

As well as being one of the world’s leading laboratories for particle physics research, CERN also played a major part in the development of internet technology. The World Wide Web began as a CERN project named ENQUIRE, initiated by Tim Berners-Leein 1989 and Robert Cailliau in 1990. More recently, CERN has become a facility for the development of grid computing, hosting projects including the Enabling Grids for E-sciencE (EGEE) and LHC Computing Grid.

“I think it says something important about the collaborative nature of science that an organization like CERN, that conducts high-energy particle collisions, can work with a company that is dedicated to completely eliminating collisions; in traffic,” said Dr Dennis Nobelius, Zenuity’s chief executive. “I personally view this collaboration as a manifestation of the fact that this rapidly developing technology not only spans across different industries, but also across the boundary between scientific research and industry, and this kind of cross-disciplinary collaboration is needed to reach ambitious goals.”

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Adam joined the company in 1994, and has been News Editor of TTT since 2009. In his other role as Circulation Manager, he helped create the original Traffic Technology International distribution list 23 years ago, and has been working on it ever since. Outside of work, he is a keen fisherman, runs a drumming band, and plays an ancient version of cricket.