Implementation of the EAR Method in Detecting Drowsiness in Vehicle Drivers:

Andy Suryowinoto; Ainur  Rohman; Wahyu Setyo  Pambudi

doi:10.21070/jeeeu.v8i1.1682

(1) * Andy Suryowinoto Institut Teknologi Adhi Tama Surabaya
Indonesia
(2) Ainur Rohman Institut Teknologi Adhi Tama Surabaya
Indonesia
(3) Wahyu Setyo Pambudi Institut Teknologi Adhi Tama Surabaya
Indonesia
(*) Corresponding Author

DOI: https://doi.org/10.21070/jeeeu.v8i1.1682

Abstract

Based on data from Polda Metro Jaya Traffic Sector, the number of traffic accidents throughout 2020 was 7,565. With a factor of 1,018 drowsy drivers or 13% of the total incidents. A solution is needed for that. The aim of this research is to calculate the average value of the duration of detection time and the number of flashes per minute, by knowing when the driver is drowsy or not drowsy. The method used is Eye Aspect Ratio (EAR), where the driver will be detected whether he is sleepy or not, by analyzing the parameters of the number of blinks per minute and the duration of the blinks. If the eyes are open (EAR value) less than 0.45 and more than or equal to 3 seconds in one blink, it is categorized as sleepy. Tests were carried out on lighting, namely: morning, afternoon, evening and night light. Test results in daylight and evening light conditions with a light intensity value of 78 lux mean the duration of drowsiness detection is 3.26 seconds and the difference in time duration with the reference theory is 0.26 seconds. Meanwhile, for night light with a light intensity value of 15 lux, the average duration of drowsiness detection is 4.04 seconds and the difference in time duration with the reference theory is 1.04 seconds. Meanwhile, the number of blinks per minute when you are sleepy is 5-8 blinks/minute and when you are not sleepy it is 13-17 blinks/minute, for morning, afternoon, evening and night light conditions. It can be concluded that overall, this system can work well for day and evening and night light conditions.

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Implementation of the EAR Method in Detecting Drowsiness in Vehicle Drivers

Implementasi Metode EAR Dalam Mendeteksi Kondisi Mengantuk Pengemudi Kendaraan Bermotor

Abstract

References