Date of Publication :4th April 2024

Abstract:In an era marked by the expansion of urbanization and increasing vehicular congestion, the demand for effective traffic management is paramount. This study introduces a pioneering Adaptive Dynamic Traffic Light Management System (DILMS) that integrates Artificial Intelligence (AI), Machine Learning (ML), and image processing. The suggested system monitors different lanes using real time data analysis via cameras vehicle identification and counting are accomplished using image analysis with the resulting counts relayed to the main processing unit the program evaluates waiting periods for specific lanes depending on vehicle numbers and then adjusts signal lights. This innovative approach significantly reduces average waiting times, improves traffic clearance efficiency, and contributes to a decrease in CO2 emissions. The system positions itself as a cutting-edge traffic management solution, leveraging the capabilities of AI and ML algorithms.

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