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Driving simulator helps to validate drowsiness detection technology

Nottingham University's Human Factors Research Group has validated BlueSkeye AI’s vehicle drowsiness detection technology for use in cars in Europe.

Driving simulator comprises an Audi TT car in an immersive curved screen
Driving simulator comprises an Audi TT car in an immersive curved screen - Nottingham University

The validation test took place in the Group’s driving simulator, which comprises an Audi TT car in an immersive curved screen. Twenty drivers spent up to an hour undertaking a monotonous driving task - following a car on a motorway - and were asked at five-minute intervals to assess their tiredness using the Karolinska Sleepiness Scale.

Drivers’ assessments of tiredness were compared to assessments of tiredness generated by Blueskeye’s machine learning algorithms in line with the official EU testing protocol. The algorithms use Near Infra-Red cameras mounted in the car’s left and right pillars to capture and analyse eye, head and facial muscle movement multiple times per second and identify early signs of fatigue.

The machine assessments of tiredness are said to have passed the EU’s threshold of 40 per cent sensitivity, indicating the ability of the system to identify instances when the driver is drowsy and achieving the standard required by the EU for inclusion in new cars.

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