The proposed method comprises a computer vision-based system highly applicable in the detection of a possible accident while driving. A stereo depth camera is placed in front of the vehicle at a point through which all crucial viewing angles are captured. The camera will be covering a viewing angle of 180°. This idea proposes an efficient framework for accurate object detection using CNN along with an object tracking algorithm. This system will determine the probability of an accident based on the three parameters, which are: object approaching towards the line of movement, relative distance between the object and vehicle, and relative speed of the object with respect to the vehicle. It will provide a reliable technique to attain an efficient rate of detection with less erroneous indication of an accident. Since it covers 180°, it can accurately detect any object/vehicle coming from either side. By judging the speed of the vehicle and the trajectory of the object, the system will calculate the expected time of collision and in order to avoid the impact, an automatic braking mechanism will take place to cautiously reduce the speed of the vehicle in a calculated manner. In conclusion, this computer vision-based system will be a game-changer in accident detection and will make driving safer, easier, and more efficient.


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    Titel :

    A Smart Driver Assistance System for Accident Prevention


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Chen, Joy Iong-Zong (Herausgeber:in) / Wang, Haoxiang (Herausgeber:in) / Du, Ke-Lin (Herausgeber:in) / Suma, V. (Herausgeber:in) / Singh, Tarush (Autor:in) / Sheikh, Faaiza (Autor:in) / Sharma, Ashish (Autor:in) / Pandya, Rahul (Autor:in) / Singh, Arpit (Autor:in)


    Erscheinungsdatum :

    2022-02-10


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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