New Software can Detect When People Text and Drive

Alerting drivers when they are dangerously distracted.

Young girl texting and driving, horizontal
Young girl texting and driving, horizontal, Image: shutterstock/Burlingham

The most common distraction while driving might be your phone. Text and drive now become a growing trend and country’s top killers as well. Drivers assume that they can text and drive and remain safe, but it 6 times more likely to cause an accident.

Scientists at the University of Waterloo have developed a software that accurately determines if drivers are engaged in other distracting activities.

This new software makes use of artificial intelligence and cameras. It detects driver’s hand movements lost normal driving behavior and grades them in terms of possible safety threats.

Scientists used machine learning algorithms to train the software. Thus, it can recognize if the driver is texting, talking on a cell phone or reaching into the backseat to retrieve something. The seriousness of the action is assessed based on duration and other factors.

Professor Fakhri Karray said, “The information could be used to improve road safety by warning or alerting drivers when they are dangerously distracted. And as advanced self-driving features are increasingly added to conventional cars, signs of serious driver distraction could be employed to trigger protective measures.”

“The car could actually take over driving if there was imminent danger, even for a short while, in order to avoid crashes.”

Scientists took inspiration from previous research on the recognition of signs, including frequent blinking, that drivers are in danger of falling asleep at the wheel. Now, scientists are looking for combining several different kinds of driver distraction in a single system.

Karray said, “It has a huge impact on society, citing estimates that distracted drivers are to blame for up to 75 per cent of all traffic accidents worldwide.”

They are in plan to make use of sensors to measure physiological signals. For example, such as eye-blinking rate, pupil size, and heart-rate variability. According to them, it will help determine if a driver is paying adequate attention to the road.