Section: Bilateral Contracts and Grants with Industry

Bilateral Contracts with Industry

VALEO Group: a very strong partnership is under reinforcement between VALEO and Inria. Several bilateral contracts were signed to conduct joint works on Driving Assistance, some of which VALEO is funding. This joint research includes:

• The PhD thesis of Pierre de Beaucorps and the post-doc of Thomas Streubel under the framework of VALEO project “Daring”

• SMART project: on the Design and development of multisensor fusion system for road vehicles detection and tracking. This project funds the internship of Alfredo Valle Bario.

• A CIFRE like PhD thesis is ongoing between VALEO and Inria (M. Maximilian JARITZ), dealing with multisensor processing and learning techniques for free navigable road detection.

• VALEO is currently a major financing partner of the “GAT” international Chaire/JointLab in which Inria is a partner. The other partners are: UC Berkeley, Shanghai Jiao-Tong University, EPFL, IFSTTAR, MPSA (Peugeot-Citroën) and SAFRAN.

• Technology transfer is also a major collaboration topic between RITS and VALEO as well as the development of a road automated prototype.

• Finally, Inria and VALEO are partners of the CAMPUS project (PIA french project) including SAFRAN, Invia and Gemalto. The aim of the project is the development of autonomous vehicles and the realization of two canonical uses-cases on highways and urban like environments.

TATA Motors European Technical Centre (TMETC): a new partnership was born in 2016 with the aim of developing a highly automated vehicle. Technology transfer from Inria to TATA Motors includes localization and mapping as well as control-command codes.

Renault Group: Collaboration between Renault and RITS re-started in 2016 and is expected to know a major growth in 2017. Three different research teams in Renault are now working separately with RITS on different topics.

A first concrete action was the beginning of a CIFRE PhD thesis funded by Renault and the French ANRT. The thesis deals with the accurate localization of an autonomous vehicle on a highway using mainly on-board low-cost perception sensors.