Localization - Augmented Reality


  • Invent, experiment with and simulate future driver/smart vehicle relations, particularly exploring the possibilities of autonomous vehicles (automobile case).
  • Contextualize relevant virtual information items within the driving scene.
  • Identify and combine location systems achieving a financial breakthrough while preserving security of operation.

New systems for driving assistance, such as augmented reality for navigation assistance (insertion of virtual data synchronized with the environment), demand a more-exact degree of location, and with greater speed than GPS can provide.

Thus, the project examines:

  • information processing and merging;
  • rendering via display technologies at the driver position, for road vehicles and rail systems. In both cases, an appropriate degree of security of operation has to be achieved (the road vehicle driver will need to be reassured that he/she can delegate driving to a non-human system);
  • human factors, to ensure effectiveness of interaction.


The purpose of this project is to analyze and develop technologies and services for information processing and visualization for the automobile and rail sectors:

  • study new interactions and interfaces between the driver (or rail system) and the vehicle, notably based on augmented reality technology;
  • study location systems procuring a cost/performance/security breakthrough.

Targeted markets

The project targets the automobile and railway markets, and the applications are:

  • exact and sure location;
  • relaying of railway trackside signaling to the driver’s cab;
  • supervising road vehicle driving;
  • road vehicle HMI (human-machine interaction) supervision;
  • HMI content/visual grammar;
  • rendering technologies.

Doctoral theses supported by the project

  •  Designing cooperation principles for autonomous driving system (Université de Valenciennes (LAMIH – CNRS / CIFRE Renault)
  • Augmented Reality adaptive Human-Machine Interface for the autonomous automotive driving (LAMIH – CNRS – LABSTIC / CIFRE Renault)

Find out more

Autonomous Transport
Industrial Partners
Alstom Transport Assystem Oktal Renault Sysnav Valeo
Academic Partners
Project Manager
Sabine Langlois