Design and implementation of an adaptive headlight system model for enhanced night-time driving safety

Night driving is risky because the glare from oncoming high beams can cause temporary blindness, known as the Troxler effect. Drivers often don’t adjust their headlights manually, or the adjustment isn’t enough. To fix this, the paper proposes an adaptive headlight system that changes the light pattern automatically. The system uses a camera mounted on the car to record video of the road ahead. A regression‑based machine learning model analyzes the video, dividing the view into a grid to find the exact position of oncoming cars. When a vehicle is detected, the system sends a signal to an electronic control unit made of an Arduino UNO, a relay module, and

a battery. This unit moves a custom reflector to dim or steer the beam away from the oncoming driver while still lighting the car’s own lane. The authors built a working hardware‑software prototype, but real‑world use would still need to solve issues like processing delay at high speeds, camera calibration in different weather, and compatibility with standard car communication networks.

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