Green Lane - Smart Signal with Emergency Priority

Abstract

Traffic congestion and delayed emergency response remain major challenges in urban transportation due to the limitations of conventional fixed-time traffic signal systems. These systems operate with predefined signal duration and failed to adapt to real-time traffic density or provide automatic priority to emergency vehicles. This paper presents “Green Lane – Smart Signal with Emergency Priority”, an intelligent traffic signal system that dynamically controls signal timing based on real-time vehicle density while enabling priority passage for emergency vehicles. The proposed system integrates camera-based vehicle detection using Python and Open CV with an ESP32 microcontroller for adaptive traffic signal control. Emergency vehicle detection triggers an immediate signal override to create a dedicated green lane, ensuring faster clearance. Experimental results obtain from a prototype implementation show reduced waiting time improve traffic flow efficiency and quicker emergency vehicle movement compared to traditional fixed time systems. The system is low-cost, scalable, and suitable for smart city traffic management applications.

Introduction

Urban traffic congestion and emergency vehicle delays are major challenges in modern cities. Traditional fixed-time traffic signals are inefficient, causing long waits, increased fuel consumption, and pollution. The proposed Green Lane system addresses these issues by dynamically adjusting signal timings based on real-time traffic density using camera-based detection and an ESP32 microcontroller. Emergency vehicles are automatically prioritized through signal overrides, creating a dedicated green lane.

The system is low-cost, scalable, and fully automated. Vehicle detection uses Python and OpenCV, with traffic data processed by the ESP32 to allocate green signal durations. Four operational modes—normal traffic, emergency priority, simulation, and analytics—ensure adaptive traffic control, emergency response, and real-time monitoring via a Streamlit dashboard. Components include USB cameras, ESP32, LEDs, and simple wiring, making deployment feasible for urban and semi-urban areas.

Compared to existing fixed-time systems, the Green Lane improves traffic flow, reduces waiting times, enhances road safety, and supports smart city traffic management.

Conclusion

The Green Lane-Smart Signal with Emergency Priority system provides an effective solution for intelligent traffic management. By combining real-time vehicle detection, adaptive signal control, and emergency priority handling, the system improves traffic flow efficiency and emergency response performance. The low-cost makes it suitable for smart city deployment.

References

[1] F. M. Talaat and S. A. Gamel, “Smart Navigation System for Emergency Vehicles,” 2025. [2] P. Harris et al., “AI-Driven Real-Time Traffic and Emergency Management using YOLO,” 2025. [3] Hesham A. Sakar & Magda I. EI-Afifi, “Intelligent Traffic and Emergency Management System,” 2023. [4] Pendurthy Bhavana et al., “IoT Based Dynamic Road Traffic Management System,” 2023. [5] Ninad Lanke & Sheetal Koul, “Smart Traffic Management System,” (2013)

Copyright

Copyright © 2025 Bhavya Shree D G, Yashwant Kumar S, Ranjith B, Mrs. Nandini M, Dr. Mohamed Saleem. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.