MargadarshiAI: A Guiding Intelligence for Real-Time Traffic Signal Efficiency for the Department of Science and Technology

Authors: Mulay Samiksha Krishna, Gorde Yash Rajendra, Bakare Purva Kishor, Mandekar Rushikesh Santosh, B. L. Gunjal

Country: India

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Abstract: Traffic congestion and road safety violations are major challenges in urban areas, leading to delays and increased risk of accidents. This project proposes an intelligent traffic management system that improves road safety and traffic flow through smart monitoring. At its core, the system manages traffic lights in a normal anti-clockwise sequence, allowing each direction of vehicles to move in a fair and predictable order, ensuring smooth traffic flow even without advanced control mechanisms. To further reduce congestion, the system incorporates density-based traffic light control and prioritizes emergency vehicles such as ambulances, fire trucks, and police cars by interrupting the normal cycle to provide an immediate green signal. This enables faster response times and ensures timely arrival during critical situations. In addition to traffic management, the system monitors road safety violations using cameras to detect helmet usage and identify triple-seat riding on two-wheelers. These detections are performed automatically without manual intervention. The system operates in real-time and minimizes the need for continuous human supervision, making it more reliable and scalable. All violations are reported to an admin panel, where authorities can view alerts, review evidence, and take appropriate actions such as issuing fines or warnings. By integrating smart traffic control with automated safety monitoring, the system reduces congestion, supports emergency services, and promotes safer road practices.

Keywords: Smart Traffic Control, Emergency Vehicle Priority, Helmet Detection, Violation Reporting, Density-Based Signals, Triple Seat Detection.

Paper Id: 233074

Published On: 2026-04-22

Published In: Volume 14, Issue 2, March-April 2026

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