If you are one of the lucky ones you're right and you make it safely to your destination. But often times drivers aren't that lucky and, unfortunately fall asleep at the wheel causing fatal accidents.
Researchers at Sandia National Laboratories are hoping to help prevent accidents like these and others caused by driver distraction by designing cars that analyze human behavior. These cars may be able to tell from your driving that you are getting tired or, if traffic's heavy to put a cell phone call on hold.
"Drivers are fitted with a caps with electrodes hooked up to a car's computer that collect physical data like brake pedal force, acceleration, steering wheel angle, and turn signaling" says Kevin Dixon, principal investigator. "Specialized sensors like a pressure-sensitive seat and ultrasonic head-trackers measure drivers' posture."
And the best part, according to Dixon, is that the team isn't doing anything new or different to the car. All the software that determines dangerous or safe driving situations would be added to vehicle's existing computers.
Researchers recently tested the device on five drivers who were hooked up to an electroencephalogram machine that measured their brains' electrical activity as they were driving. Researchers collected hours of data in unstructured driving conditions and inputted into Sandia software. The data, referred to as classifiers, categorized driving behavior and could detect driving situations like approaching a slow-moving vehicle or changing lanes in preparation to pass another vehicle.
The system detects the difficulty and resulting stress from tasks drivers are attempting. It then tries to modify the tasks and environment to lower the stress and improve performance parameters. Similar experiments were conducted for off-road drving where conditions were much less structured than typical roadways.
More experiments took place at Camp Pendelton with Marine Corps personnel driving a modified military vehicle. Both drivers and passengers were fitted with EEGs and the software classifier determined how difficult the driving situation was and who was better suited to perform the task. For example, during a difficult maneuver, it might be best for the passenger to receive radio transmissions so the driver isn't distracted.
"If our algorithms can identify and alert drivers to dangerous situations before they happen, we will help save lives," says Dixon.