Brain-machine Interface for drivers

Far reaching research on Brain Machine Interface (BMI) systems by scientists at EPFL already allows users with motor disabilities to maneuver their wheelchairs by thought decoding alone. This project aims at adapting these BMI approaches to the car – and driver – of the future.

The project proposes the application of Brain Machine Interface (BMI) technology to ease the interaction with intelligent cars in order to enhance the driving experience. Ranging from parking and lane changing assistance to fully autonomous navigation, today’s cars can autonomously assess road conditions and either perform or assist different driving maneuvers.

In our approach, instead of removing the human from the loop, the BMI monitors the driver’s cognitive state. This information is critical for modulating the assistance provided by the intelligent car. Future cars will take into account the external context (as perceived by in-car sensors) and the user’s intention (as decoded from electroencephalographic signals, EEG) to provide suitable and timely assistance; seamlessly interacting with the driver.

This research project lasted four years and was conducted by the Chair in Non-Invasive Brain-Machine Interface (CNBI), directed by Prof. José del R. Millán. The CNBI has an internationally recognized expertise in the direct use of human brain signals to control devices and interact with our environment. This project has been sponsored by Nissan Motor Co. Ltd.

Principal investigator Prof. José del R. Millán
Project manager Ricardo Chavarriaga
Sponsor Nissan
Period 2010-2014
Laboratory CNBI
Collaboration TRACE