Connected vehicles are set to become a pervasive reality in the upcoming years. Despite the emergence of this trend, providing seamless connectivity and computing services to vehicles reveals a challenging task, requiring coordinated work between numerous players and the integration of the respective technologies.
FLOYD, a Research & Innovation (R&I) project led by Capgemini Engineering, has the main purpose of building such a technological stack for offering high-performance network/computation services to vehicular users. Through the collaboration between complementary R&I industrial and academic entities, FLOYD will enable the development, validation, and exploitation of a variety of components and technologies, addressing multiple unanswered interrogations between vehicular and network communications.
FLOYD innovation potential is leveraged by the comprehensive technological approach of this project, where novel developments in the area of Artificial Intelligence are combined with breakthrough technologies in the area of edge computing and 5G, which will allow developing a framework of tools for networking and communications to support platooning applications.
It is relevant to highlight the following innovative characteristics:
This project aims to improve mobility services and accelerate the integration of autonomous driving in society, by advancing the networking and computation technological basis on which complex mobility and autonomy services and functionalities can be built.
Capgemini Engineering – Raquel Pinho
ALTICE LABS, S.A. – Rui Calé
Computer Science Department – Peter Steenkiste
FLOYD aims to build an integrated demonstrator able to showcase the coordinated operation between all these components and technologies in a real-world use-case scenario.
The technological research and development lines are based on two main driving forces: Artificial Intelligence and Platooning Applications. In this project, the entities will explore the potential of Artificial Intelligence in multiple technological domains, by identifying processes in mobility, autonomous driving, or network operation that follow complex behaviors and require an intelligent learning approach. Underlying all the tech development, a down-to-earth, use-case of vehicular platooning motivates the developed applications, testbed, and demonstrator.