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PRYSTINE

Programmable Systems for Intelligence in Automobiles

Basic data

Field

European

Date

01/05/2018 - 30/04/2021

Industry

Transporte, almacenamiento y logística

Budget

Total project budget: 50 M€ ITI budget in the project: 206.637,81€.

Funded by

European Commission - H2020 ECSEL

Website

Video

PROJECT INFORMATION

DESCRIPTION

Project in the field of intelligent mobility and reduction of energy consumption oriented towards the development of autonomous vehicles. Vehicle automation, with the ultimate goal of achieving fully autonomous driving, has been identified in Europe as one of the most impactful issues in the coverage of the Grand Societal Challenges in the areas of intelligent transport and energy efficiency. Currently, one of the biggest challenges to achieve autonomous driving is to go beyond SAE (Society of Automotive Engineers) level-2, which currently incorporates some commercial cars offering fairly limited automation, and reach SAE level-3. At this level the car should be able to control longitudinal displacement and lateral movement, as well as automatic detection and reaction to objects and driving-related eventualities, although the driver is still required in cases where the automation chain reaches its operational limit or an unforeseen failure occurs.

Impact

Improve the reliability and performance of the components that make up FUSION, while reducing costs and energy consumption.
Increase the reliability of embedded control in FUSION based on the integration of signal processing and Artificial Intelligence methods, combining high performance processors with dedicated controllers, exploiting innovative hardware/software/firmware partitioning methods.
Improve and adapt the electrical/electronic architecture of the vehicles to facilitate the integration of FUSION, allowing the benefits of the new components to be passed on to the end user.
Develop fault-tolerant systems for urban and rural environments based on FUSION, whose implementation will focus on the fusion of sensors at different levels of abstraction and the use of artificial intelligence methods and conventional algorithms running on intelligent embedded platforms.