5GMETA: R&D Live Training Loop

Overview of the 5G-META use case on R&D Live Training Loop

5G enables online sensor data sharing from car fleets to a central server. This expedites the traditional R&D pipeline used in Autonomous Driving, based essentially on collecting datasets, training new machine learning models and testing these new models against datasets. This pipeline is run in loop, until satisfactory results are obtained. Currently, the datasets are stored locally in the car, and then moved to the laboratory in a hard disk. TIER1 and OEM car fleets are geographically distributed across the whole European continent, so the process can get quite slow. However, 5G enables sending the raw sensor data to a central server in real time. Not only this, but models can also be updated both in the cloud and in the car on demand, improving significantly the current process. This process optimisation can reduce the already quite high R&D costs of CAM, and technical innovation can also be used for other purposes such as forensics analysis to clarify product liability.
 

Partner ecosystem: VICOTECH (Spain); AKKA HIGH TECH (France); DEKRA TESTING AND CERTIFICATION SAU (Spain); ERTICO (Belgium); CNIT (Italy); INTEMPORA (France); LIFTT SPA (Italy); FONDAZIONE LINKS (Italy); NEO GLS (France); INSTITUT VEDECOM (France); WIND TRE SpA (Italy) 

Funding reference: Horizon 2020; ICT-42-2020 - 5G PPP – 5G core technologies innovation

Funding cycle: September 2020-August 2023

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