Road accidents have reached an all-time high in today’s fast-paced world. Side-impact collisions and side-swipes are the most common types of road accidents. These accidents usually happen at intersections with little traffic and no traffic lights. Cars approaching the crossroads from different directions cannot see each other and may approach at high speeds. As a result, when the drivers notice the car at the crossroads, it is too late to apply the brakes, and an accident is unavoidable. As a result, to address such a life-threatening issue, we devised a strong solution. The process begins with the installation of a traffic signal-like pole that will support the main component. The main component consists of four signal lights and four cameras, each pointing the four crossroads directions. Real-time vehicle detection will take place using Machine Learning and Computer Vision, which will calculate both the distance of the vehicle from the crossroad and the speed with which it is approaching. When a car approaches the crossroads speedily, the lights on the other roads turn red, alerting vehicles on the other roads about the approaching vehicle. The signal will remain green if all roads are empty.


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    Titel :

    Crossroad accident prevention system using real-time depth sensing


    Beteiligte:


    Erscheinungsdatum :

    2023-10-06


    Format / Umfang :

    349124 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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