IOT Based Smart Traffic Management System

Abstract

One of the significant challenges faced by major cities today is traffic management. The possible reason for this can be the increasing number of vehicles, lack of proper infrastructures, improper roads, growing population etc. Increased accidents and pollution levels have been observed as the most common problems in major cities. All this gives rise to the need of IOT based Traffic control system which continuously detects, monitors, and adjusts traffic signal timings according to traffic load. This paper describes methods for controlling and monitoring traffic.

Introduction

Modern cities face severe traffic congestion due to vehicle volumes exceeding road capacity, leading to traffic jams, accidents, and increased pollution. Traditional traffic signal systems use fixed-time signals, which are inefficient for dynamic traffic conditions and cannot prioritize emergency vehicles, resulting in delays.

Need for IoT-based Traffic Control:
An IoT-based traffic management system can monitor real-time traffic, adjust signal timings according to vehicle flow, and prioritize emergency vehicles by clearing their lanes. Benefits include reduced congestion, shorter travel times, lower travel costs, less reliance on traffic police, and improved overall road safety.

Literature Review – Approaches in Smart Traffic Systems:

1. Camera-based system (Shashank S): Uses image data and algorithms to dynamically set traffic signals.

2. PLC & weight sensors (Priyanka Sharma): Signals respond to lane load, reducing congestion and detecting overloaded vehicles.

3. RFID system (Mr. Ninad Lanke): Each vehicle has an RFID tag; traffic flow is counted automatically to adjust signals.

4. Image processing (R Srinivasan): Real-time congestion monitoring; fast but resource-intensive and costly.

5. Client-server model (Mr. Abubakar Muhammad): Calculates traffic based on speed, position, etc., reducing vehicle waiting time.

6. Ultrasound + image processing on Raspberry Pi (Harsha J): Sensor-based dynamic signal allocation based on vehicle density.

Conclusion

The IoT-based traffic control system represents a transformative solution to urban traffic congestion and road safety challenges. Through cutting-edge sensor technologies and real-time data analytics, the system offers a scalable approach to modern traffic management. By continuously monitoring traffic density and dynamically adjusting signal timings, it effectively alleviates congestion and enhances transportation efficiency. The system\'s manual control features, including prioritizing emergency vehicles, ensure swift response to changing traffic conditions, bolstering public safety. Looking forward, the project presents opportunities for further advancement and expansion. By integrating emerging technologies and fostering collaboration with stakeholders, it can drive widespread deployment and adoption. In essence, the IoT-based traffic control system heralds a new era in urban mobility, characterized by data-driven insights and user-centric solutions. It holds the promise of safer, more efficient, and sustainable transportation networks, ultimately enriching the quality of life for residents and visitors in cities worldwide.

References

[1] Bhuvan S T, Manjunath H.R , Abhiman H.R, Ranjan Kumar, Sachin G Rao, “Smart Traffic Management System: A Literature Review” International Journal of InnovativeResearch in Electrical, Electronics, Instrumentation and Control Engineering ,Impact Factor 7.047Vol. 10, Issue 2,February 2022 [2] Sundar, R., Hebbar, S. and Golla, V, “Implementing intelligent traffic control system for congestion control,ambulance clearance, and stolen vehicle detection”, IEEE Sensors Journal, Vol. 15, No. 2, pp. 1109-1113, 2015 [3] Chowdhury, A.; “Priority based and secured traffic management system for emergency vehicle using IoT” Engineering MIS (ICEMIS), International Conference on, IEEE.,(2016). [4] Milanes, V., Villagra, J., Godoy, J., Simo, J., Pérez, J. andOnieva, E.;”An intelligent v2i-based traffic management system” IEEE Transactions on Intelligent Transportation Systems, Vol. 13, No. 1, (2012). [5] Shashank S, Kiran P, Nischay D, Vinay Kumar M, B R.Vatsala, Dr. C. V.Raj;”IOT Based Traffic Management System” International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT) [6] P.Sharma, A. Goen “Smart traffic controls system using weighted data” International conference on advanced computation and telecommunication 2018 [7] N. Lanke and S. Koul, “Smart Traffic Management System”, International Journal ofComputer Applications (0975 – 8887) Volume 75– No.7,August 2013. [8] I. Gulati and R. Srinivasan,”Image Processing In Intelligent Traffic Management” International Journal ofRecent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8 Issue-2S4, July 2019. [9] A. M.Miyim, M.M.Alhaji;”Smart Traffic Management System”; 2019 15th International Conference on Electronics, Computer and Computation (ICECCO) [10] H. J.Nafea, N. Nair;”Density Based Smart Traffic System with Real Time Data Analysis Using IoT”; 2018 International Conference on Current Trends towards Converging Technologies (ICCTCT)

Copyright

Copyright © 2025 Vanshika Patel, Viraj Shah, Dhyey Sampat, Sonal Dubal. 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.