Skip to main content

New software could detect when people text and drive

Engineering researchers at Canada’s University of Waterloo are developing technology which can accurately determine when drivers are texting or engaged in other distracting activities. The system uses cameras and artificial intelligence (AI) to detect hand movements that deviate from normal driving behaviour and grades or classifies them in terms of possible safety threats.
September 20, 2017 Read time: 2 mins
Engineering researchers at Canada’s University of Waterloo are developing technology which can accurately determine when drivers are texting or engaged in other distracting activities. The system uses cameras and artificial intelligence (AI) to detect hand movements that deviate from normal driving behaviour and grades or classifies them in terms of possible safety threats.


Fakhri Karray, an electrical and computer engineering professor and director of the Centre for Pattern Analysis and Machine Intelligence (CPAMI) at Waterloo, said that information could be used to improve road safety by warning or alerting drivers when they are dangerously distracted. As advanced self-driving features are increasingly added to conventional cars, he said, 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,” said Karray.

Algorithms at the heart of the technology were trained using machine-learning techniques to recognise actions such as texting, talking on a cellphone or reaching into the backseat to retrieve something. The seriousness of the action is assessed based on duration and other factors.

That work builds on extensive previous research at CPAMI on the recognition of signs, including frequent blinking, that drivers are in danger of falling asleep at the wheel. Head and face positioning are also important cues of distraction.

Ongoing research at the centre now seeks to combine the detection, processing and grading of several different kinds of driver distraction in a single system.

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

Related Content

  • July 30, 2021
    AI is creating road maintenance savings
    Artificial intelligence is starting to create savings for hard-pressed local authorities when it comes to road maintenance. David Crawford reviews recent advances in cost and performance control
  • June 4, 2025
    Are we nearly there yet? The rise and rise of AI in WiM
    The technology of artificial intelligence has moved on quickly since ITS International last asked the Weigh in Motion community in 2022 - so how is AI used in the WiM sector now? We asked four experts...
  • March 4, 2016
    Report finds 87 per cent of US drivers engage in unsafe driving behaviour
    About 87 per cent of drivers in the US engaged in at least one risky behaviour while behind the wheel within the past month, according to latest research by the AAA Foundation for Traffic Safety. This includes driving while distracted, impaired, drowsy, speeding, running red lights or not wearing a seat belt. These results come as nearly 33,000 Americans died in car crashes in 2014, and preliminary estimates project a nine percent increase in deaths for 2015. The report finds that one in three drivers ha
  • November 23, 2018
    Cut freight deliveries – improve Southampton’s air quality
    Taking the pressure off cities’ road networks can have a beneficial effect on the environment. David Crawford looks at a new economic model which seeks to quantify the societal effect of freight traffic in Southampton, one of the UK’s five most polluted cities Cuts of 60% or more in volumes of freight deliveries are being predicted - along with badly-needed improvements in air quality - from a load consolidation scheme currently being introduced in the UK port city of Southampton. The forecasts are based o