An Intelligent Traffic Control System for Emergency Vehicles

Abstract

This paper presents the design and development of an intelligent traffic control system designed to provide priority to emergency vehicles and enhance overall flow of traffic in urban environments. The proposed system integrates the RF communication technology with Arduino IDE boards to enable real-time communication amongst emergency vehicles and traffic signals. By utilizing RF transmitters, the system creates a green wave for emergency vehicles, allowing them to move through traffic intersections without delay. The control system operates in both manual and automatic modes, providing flexibility for traffic personnel to override or automate signal control depending on the situation. The dual-mode functionality ensures quick, reliable communication and reduces waiting time for emergency vehicles, addressing critical delay times. The system’s design offers a practical solution for improving emergency response times while managing urban traffic congestion.

Introduction

Urban traffic congestion often leads to delays, fuel wastage, and increased pollution, posing serious risks for emergency vehicles like ambulances and fire trucks. The proposed solution introduces an Intelligent Traffic Control System that prioritizes emergency vehicle movement using Arduino microcontrollers and RF communication technology.

System Overview

• The system supports both manual and automatic modes.

  • Manual Mode: Enables traffic personnel to override signals during special events or emergencies.

  • Automatic Mode: Emergency vehicles equipped with RF transmitters communicate with RF receivers at traffic lights, triggering a synchronized “green wave” that clears their path.

• The system uses RFID tags for vehicle identification and Arduino Uno boards for signal control.

• Implemented across four-lane intersections (Nodes A, B, C, and D), the system dynamically adjusts signal lights to prioritize emergency vehicles, ensuring faster and safer transit.

Literature Insights

• Prior works highlight the role of AI, V2V and V2I communication, fuzzy logic systems, IoT, and automated traffic sensors in improving traffic flow and safety.

• The "Green Wave" technique and multi-agent systems have shown success in reducing congestion and enhancing traffic efficiency.

Methodology

1. Hardware Setup: Uses RFID readers, RF modules, LEDs, and relays integrated with Arduino.

2. Communication: RF modules enable secure, low-power wireless interaction between vehicles and intersections.

3. Signal Control: Traffic signals turn green for the approaching emergency vehicle and adjust red/yellow lights in other lanes to avoid conflict.

4. Testing: Verified the real-time functionality of green wave activation and signal reversion after the vehicle passes.

Results & Discussion

• The system successfully detected emergency vehicles and changed traffic signals accordingly.

• Demonstrated a green wave effect where signals along the vehicle’s route turned green sequentially.

• Significantly reduced delay for emergency vehicles, improving response time and safety.

• Ensures minimal disruption to regular traffic by periodically updating non-prioritized lanes.

• The system is cost-effective, scalable, and suitable for real-world urban deployment.

Conclusion

The design and development of the Intelligent Traffic Control System for Emergency Vehicles underscores the transformative capability of combining Arduino microcontrollers with RF communication technology in urban traffic management. This innovative system effectively prioritizes emergency vehicles, significantly minimizing delays that could have critical, life-threatening implications. By employing real-time signal adjustments and a green wave mechanism, the system not only enhances the efficiency of emergency responses but also maintains overall traffic flow, ensuring that other lanes are managed effectively. The adaptability, cost-effectiveness, and scalability of this system makes it a practical solution for modern urban environments, thus helping achieve improved public safety and improved, efficient traffic management strategies. Ultimately, this approach promises to enhance emergency response times and contribute to safer, more responsive city traffic systems.

References

[1] Rajeshwari S., Santhosh Hebbar, Varaprasad Golla, Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance and Stolen Vehicle Detection, IEEE Sensors Journal, vol. 15, no. 2, February 2015, Pages1109-1113. [2] [2] Conde Bento, Luis & Parafita, Ricardo & Nunes, Urbano. (2012). Intelligent traffic management at intersections supported by V2V and V2I communications. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. 10.1109/ITSC.2012.6338766. [3] [3] Wang Wei and Fan Hanbo, \"Traffic accident automatic detection and remote alarm device,\" 2011 International Conference on Electric Information and Control Engineering, Wuhan, 2011, pp. 910-913, doi: 10.1109/ICEICE.2011.5777923. [4] [4] GuojiangShen,\"Urban Traffic Trunk Two-direction Green Wave Intelligent Control Strategy and Its Application \", Intelligent Control and Automation,2006. WCICA 2006. The Sixth World Congress. Volume:2 Publication Year: 2006, Page(s): 8563 8567. [5] [5] Balaji Parasumann, Dipti Srinivasan, Distributed Geometric Fuzzy Multi agent Urban Traffic Transaction. Intelligent Transportation Systems, Volume 11 Issue 3, September 2010, Pages714- 727. [6] [6]. WantaneeViriyasitavat and Ozan K. Tonguz Priority Management of Emergency Vehicles at Intersections Using Self-Organized Traffic Control, Vehicular Technology Conference(VTCFall),2012IEEE. [7] [7]. ER. Kaushik Babhure, MS. Mona Mulchandani, Dr. Pradnya Borkar “Smart Traffic Management for Emergence Vehicles Using Sound Detection”, International Journal of Future Generation Communication and Networking Vol. 13, No. 2s, (2020), pp. 1226– 1229. [8] [8] P. Lavanya, KalluriPooja, RiyaYasmeen, RevuSupriya “ Traffic Management For Emergency Vehicles Based On Visual Sensing” International Journal of Creative Research Thoughts (IJCRT) Volume 11, Issue 6 June 2023. [9] [9] K. D. S. A. Munasinghe, T. D. Waththegedara, I. R. Wickramasinghe, H. M. O. K. Herath and V. Logeeshan, \"Smart Traffic Light Control System Based on Traffic Density and Emergency Vehicle Detection,\" 2022 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, 2022, pp. 1-6, doi: 10.1109/MERCon55799.2022.9906184. [10] [10] Sangamesh S B, Sanjay D H, Meghana S, M N Thippeswamy “Advanced Traffic Signal Control System for Emergency Vehicles” International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8 Issue-3, September 2019. [11] [11] Sarala. T, Sunitha. S V and Ashwini. S. Savanth, \"Integrated Traffic Control System for Emergency Vehicles,\" 2024 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), Bangalore, India, 2024, pp. 1-5, doi: 10.1109/IITCEE59897.2024.10467245.

Copyright

Copyright © 2025 Thanishka K, Sarala T, Kiran K N , Tanzeem Pasha, Ujwal B S, Varun Sameeran Namavali. 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.