Future’s Mind-Reading Cars Could Brake 130 Milliseconds Before the Driver’s Move
German researchers have used drivers’ brain signals, for the first time, to assist in braking, providing much quicker reaction times and a potential solution to the thousands of car accidents that are caused by human error.
The study, published 28 July 2011 in Journal of Neural Engineering, identified the parts of the brain that are most active when braking and used a driving simulator to demonstrate the viability of mind-reading assisted driving.
Many high-end cars today come equipped with brake assist systems, which help a driver use the brakes correctly depending on particular conditions in an emergency. But what if the car could apply the brakes before the driver even moved?
This is what German researchers have successfully simulated, as reported in the Journal of Neural Engineering. With electrodes attached to the scalps and right legs of drivers in a driving simulator, they used both electroencephalography (EEG) and electromyography (EMG – a technique for evaluating and recording the electrical activity produced by skeletal muscles) respectively to detect the intent to brake. These electrical signals were seen 130 milliseconds before drivers actually hit the brakes—enough time to reduce the braking distance by nearly four meters.
Seated facing three monitors in a driving simulator, each subject was told to drive about 18 meters behind a computer-driven virtual car traveling at about 100 kilometers per hour (about 60 mph). The simulation also included oncoming traffic and winding roads. When the car ahead suddenly flashed brake lights, the human drivers also braked. With the resulting EEG and EMG data, the researchers were able to identify signals that occurred consistently during emergency brake response situations.
“None of these [signals] are specific to braking,” says Stefan Haufe, a researcher in the Machine Learning Group at the Technical University of Berlin and lead author of the study. “However, we show that the co-occurrence of these brain potentials is specific to sudden emergency situations, such as pre-crash situations.” So while false positives from the signal are possible, the combination of EEG and EMG data makes a false positive much less likely.
While this kind of brain and muscle measurement works in lab conditions, the next step—real-world application—will likely be much more difficult technically to arrange. The first thing Haufe and his team will investigate is whether or not it’s possible to accurately gather data from EEG and EMG measurements in a real-world condition. In the lab, participants were asked not to move while attached to the wires, but real-world drivers move around however they please.
Although research into mind-reading-assisted braking systems will continue, tests involving real vehicles are likely many years away. The research may never lead to a fully automated braking system, but it could ultimately result in a system that takes brain data into account when implementing other assisted-braking measures.