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A Smart Car That Can Read Brain Signals

Jun 24, 2020 | Industry Trends

EPFL (Ecole Polytechnique Fédérale de Lausanne, Frace) and Nissan researchers are able to read a driver’s brain signals  and send them to a smart vehicle so that it can anticipate the driver’s  moves and facilitate the driving process. Nissan recently unveiled this  Brain-to-Vehicle (B2V) Technology

Future cars will be both self-driving and manual. “We wanted to  harness technology to enhance drivers’ skills without interfering with  the enjoyment of being behind the wheel,” explains José del R. Millán,  who holds the   (CNBI). As part of a joint project with Nissan researchers based at the  CNBI, the team managed to read the brain signals that indicate a driver  is about to do something – such as accelerate, brake or change lanes –  in order to send that information to the vehicle. With this advance  notice of a few hundreds of milliseconds, the smart vehicle can  anticipate the driver’s movements and make the ensuing maneuver easier.  The car is also equipped with sensors to monitor its environment, which  means it can help the driver when traffic conditions are difficult. 

An easier and more personalized driving experience

The  signals produced in the driver’s frontal motor cortex are detected  using a sensor-equipped EEG (electroencephalography) headset. They are  then sent to the smart vehicle for processing. By combining that data  with the information detected by its own sensors, the car can react to  the situation at hand. “If you’re coming to a red light and getting  ready to brake, the car will assist you by starting to brake 200–500  milliseconds before you do. But if you approach a red light and your  brain shows no intention of slowing the car down, the car will warn you  that the light is red to make sure you’ve seen it,” says Millán.

We  all generate different patterns of brain signals, so the vehicle learns  from each driver and customizes its software. It stores each driver’s  regular routes, as well as their driving habits and style, using this  information to more accurately anticipates what each driver might do at  any time. The brain-machine interface not only makes driving easier, it  also creates a more personalized experience, as the car will always be  in sync with the driver. Even the car’s setting can be transparently  adapted to the driver’s preferences. For instance, if the driver has  adopted a more relaxed driving style, the interface will detect that the  selected sports mode is not appropriate and switch the car to a more  comfortable setting.

Tech transfer

In  2014, after four years of research, scientists from the CNBI delivered  the brain-machine interface to their industry partner Nissan. The  carmaker then continued the research through a senior innovation  research program with support from the CNBI. The resulting technology  was integrated into a prototype, creating the interface that enables the  vehicle to communicate with the driver. This prototype was unveiled at  the Consumer Electronics Show in Las Vegas in January.

Since  2015, Nissan and the CNBI researchers have been working on further  developing this brain-vehicle technology, mainly by adding an eye  tracker function. “Our eyes are always moving and observing what’s going  on around us,” says Millán. “But not everything we see is relevant or  important. So we are studying ways to detect brain signals that indicate  that a certain object or situation has caught our attention and needs  to be factored in by the vehicle.”

For several years now,  Millán’s team has been developing scientific knowledge in detecting and  using brain signals to control objects and our environment. They have  been focusing on driver-assist technology with Nissan since 2011. In  parallel, they have been exploring other applications for their  expertise as well, such as helping people with motor disabilities.

 

 

 

 

Original Article by EPFL (Ecole Polytechnique Fédérale de Lausanne, Frace) and “Nissan Brain-to-Vehicle technology redefines future of driving”/ Koji Okuda/ 2018

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