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ADAS to Autonomous: Tiredness Recognition System

Tiredness recognition system is a proposed solution to reduce fatigue related fatalities and accidents. Companies are working to create innovative and proactive technologies that provide real safety benefits. Some of these innovative solutions are already commercially available, such as the measurement of brain activity (electroencephalogram), measurement of the eye behaviour, gaze direction, heart rate variability and micro-correction in the steering and throttle use.

These technologies allowed various car manufacturers and tech companies to work together and add new safety features to new car models:

  • NVIDIA is developing the co-pilot, an AI (artificial intelligence) tool that can learn the behaviours of individual drivers and determine abnormal behaviour;
  • Plessy Semiconductors developed sensors to be placed in a seat, to monitor changes in the heart rate;
  • Bosch is developing a camera based system that will monitor head and eye movements, body posture, heart rate and body temperature;


  • Valeo is developing an infrared camera system that will monitor children in the rear seat as well as the driver’s shoulder, neck and head movements, looking for deviations from the norm;
  • Mercedes’ Attention Assist monitors a driver’s behaviour for the first 20min behind the wheel to get a baseline of behaviours. The system then checks those against as many as 90 indexes such as the steering wheel angle, lane deviation and external factors like wind gusts and hole avoidance;
  • Volkswagen has incorporated a system to assist drivers when behind the wheel. The system monitors behaviour alerting for deviations that may be signs of fatigue;
  • Volvo has developed Driver Alert Control, a system that detects fatigue and warns drivers before they fall asleep behind the wheel;
  • Seat also developed its own tiredness recognition system that alerts a driver when there are erratic steering wheel movements and/or lane deviations.

Stanford University has been developing a research concluding that technology relying on eyelid movement can be effective in determining driver fatigue.


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