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Adaptive Headlamp and Side Mirror using Linear Regression based on Raspberry Pi3

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  • Rahul Ekatpure

Abstract

The greatest number of fatal traffic accidents occurs on curved roads at nighttime. In most cases, the late recognition of objects in the traffic zone plays an important role. This highlights to the importance of the role of automobile forward lighting systems. This paper developed a proto-type auto adjustable headlamp and mirror tilt to improve cost and reliability. Also, an adaptive mirror is implemented to remove the blind spots while taking turns. The methodology used here adaptive headlamps and mirrors are developed using Raspberry Pi3 as hardware and Python is used as programming language. Machine learning algorithm “Linear regression” is used for computing the output. Machine Learning Linear regression is considered here as it simple and efficient algorithm in terms of implementation and memory usage. Easily available components like Raspberry Pi3, LDR Sensor, ADXL Gyroscope are used and the design is developed to provide the steering mechanism for the headlamps and mirror which are actuated along with the steering of the front wheels. Around 15% increase in the illuminated area on road and 20% increase in the side mirror view is achieved.

Suggested Citation

  • Rahul Ekatpure, 2024. "Adaptive Headlamp and Side Mirror using Linear Regression based on Raspberry Pi3," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 5(1), pages 73-80.
    • Handle: RePEc:das:njaigs:v:5:y:2024:i:1:p:73-80:id:171
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