Some of the major causes that lead to road accidents are drowsiness, fatigue, or distraction of the driver. Drowsiness has become a growing problem with long distance drivers. The primary causes of drowsiness are long shifts at work and sleep deprivation. Sometimes, transport companies do not rotate drivers regularly between shifts. Thus, due to driving for an extended period, they feel sleepy. Such cases may lead to fatal accidents that may cause many casualties (for travel companies), tragic loss to a family, loss of goods (for goods transport companies), and may also cause massive economic losses. The signs of distraction and sleepiness in a driver can be discerned through their facial posture. The most popularly used methods to detect drowsy feeling of the driver are by calculating Eye Aspect Ratio (EAR) and Yawn Aspect Ratio (YAR) using landmarks of the face. The system activates alarm once the features extracted from the facial and body landmarks exceed generalized threshold value. In addition to EAR and YAR, the system includes features like Front Tilt Ratio, Side Tilt Angle, and Head-Shoulder Ratio. These features collectively contribute to detect the steadiness of driver. Experiments show that the algorithm has 91.8% detection accuracy. Our proposed solution aims to overcome the shortcomings in drowsiness detection.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    An Image Processing Approach to Enhance Driver Distraction and Drowsiness Detection Algorithm


    Contributors:


    Publication date :

    2024-03-01


    Size :

    3042282 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Driver Distraction and Drowsiness Detection System

    Roshini, G. / Kavya, Y. / Hareesh, R. et al. | IEEE | 2021



    Driver drowsiness detection

    YANG HSIN-HSIANG / PRAKAH-ASANTE KWAKU O | European Patent Office | 2015

    Free access

    Driver Drowsiness Detection

    Satish, K. / Lalitesh, A. / Bhargavi, K. et al. | IEEE | 2020


    Driver Drowsiness Detection Using Haarcascade Algorithm

    V. Sharath / N. Meghana / Nayaz, Mohammed et al. | BASE | 2020

    Free access