Regular headlight systems usually fail to offer clear visibility on bendy roads and tend to misalign when the car is overloaded, which creates blind spots and is potentially hazardous. Misaligned headlamps may cast beams into other drivers' eyes while driving in the opposite direction, causing glare and possible accidents. Lacking the ability to adapt to various driving conditions, conventional headlights tend to fail to ensure adequate visibility while driving at night. LUMO Drive is a smart headlight control technology that enhances road safety by identifying actual driving conditions in real-time and automatically changing vehicle headlights according to steering direction and vehicle loading. Unlike conventional headlights, LUMO Drive responds to various driving conditions, delivering optimal lighting on the road and minimizing glare to other drivers. In the suggested system, a MATLAB Simulink model supports extensive simulation based on the CNN-RL algorithm. The model is fed input from datasets that capture steering angle and different driving conditions, including sharp turns, steep slopes, and uneven loads. This context- dependent input enables the system to make decisions based on context and dynamically control the headlights accordingly. To ensure better performance in all conditions, the LUMO Drive system calculates the necessary headlight angle adjustments based on recognized driving situations and vehicle movements, optimizing lighting automatically. Furthermore, a prototype model is built using affordable sensors like a steering angle sensor and load angle sensor, which provide input to the microcontroller for precise, situation-based headlight adjustments, eliminating the need for expensive Suspension Height Levelling sensors. By constantly adapting to driving conditions and recognizing critical situations, LUMO Drive improves visibility, especially at night and on challenging roads, offering a safer, smarter, and more affordable lighting solution for vehicles.


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    Titel :

    LUMO DRIVE - A Smart Headlight System with Situation-Aware Sensing and Adaptive Control


    Beteiligte:
    U, Vinothkumar (Autor:in) / R, Aashika (Autor:in) / H, Abishak S (Autor:in) / E, Kiruthik N (Autor:in) / P, Kiruthika (Autor:in)


    Erscheinungsdatum :

    25.06.2025


    Format / Umfang :

    781390 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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