The traffic signals in many countries are controlled by traffic police manually. Conventional traffic light system is based on fixed time allotment at each side of the junction which cannot be varied as per varying traffic density. This existing system is not intelligent enough to make perfect decisions in varying the signal timings. The proposed system is to develop a smart density based dynamic traffic signal system. This system has ultrasonic sensors placed on dividers to detect the traffic density on each road and changes the signal timing as per the traffic density classification low, medium and high. It also paves way for emergency vehicles by making use of RF transceiver where the emergency vehicle driver sends RF signal and the signal is changed to green for that particular path. The entire system maintains free flow of traffic without manual operations and also optimizes waiting time for the emergency vehicles. Regulating the traffic through this system is inexpensive and it provides better traffic control.

Traffic density, Emergency Vehicles, Ultrasonic Sensors, RF Signal, Timer, Traffic congestion

[1] A. KirushnaKumar, M. Arun, A. Kirubanand, S. Mukesh, Aravindan Sivakumar. A, “Smart Traffic Control Systems”, International Journal for Research in Applied Science & Engineering Technology, Vol. 4, Issue IV, pp.314-320,2016.
[2] H. Peyrebrune, A.L.C. de Cerreño, “Security Applications of Intelligent Transportation Systems: Reflections on September 11 and Implications for NewYork State”, A Report to the Legislature by the NYU Wagner Rudin Center for Transportation Policy and Management, New York, July 2002.
[3] Y. J. Zheng, W. Ritter, R. Janssen, “An Adaptive System for Traffic Sign Recognition”, In the proceedings of IEEE Intelligent Vehicles Symposium 94, Paris, France, pp.165-170,1994.
[4] L. Studer, M. Ketabdari, G. Marchionni, “Analysis of Adaptive Traffic Control Systems Design of a Decision Support System for Better Choices”, Journal of Civil & Environmental Engineering, Vol. 5, Issue 6, pp. 1-10, 2015.
[5] M. Tubaishat, Y. Shang, H. Shi, “Adaptive Traffic Light Control with Wireless Sensor Networks”, In the proceedings of Consumer Communications and Networking Conference (CCNC 2007) 4th IEEE, Las Vegas, NV, USA, pp.187-191.
[6] G. Lakshminarasimhan, V. Parthipan, Mohammed Irfan Ahmed, S.H.K Nvm, D. Dhanasekaran., “Traffic Density Detection and Signal Automation using IOT”, International Journal of Pure and Applied Mathematics, Vol.116, Issue 21, pp.389-394,2017.
[7] Z. Shuai, Songhwai Oh, M-H. Yang., “Traffic Modeling and Prediction using Camera Sensor Networks”, In the proceedings of 2010 4th ACM/IEEE International Conference on Distributed Smart Cameras(ICDSC), Atlanta, Georgia, pp. 49-56, 2010.
[8] N. Lanke, S. Koul., "Smart Traffic Management System", International Journal of Computer Applications, Vol. 75, Issue 7, pp.19-22, 2013.
[9] M.K. Abbas, M.N. Karsiti, M. Napiah, B.B. Samir, M. Al-Jemeli., “High Accuracy Traffic Light Controller for Increasing the given Green time Utilization”, Journal of Computers and Electrical Engineering, Vol. 41, Issue C, pp. 40-51, 2015.
[10] S. Jeon , E. Kwon, I. Jung, “Traffic Measurement on Multiple Drive Lanes with Wireless Ultrasonic Sensors”, Sensors Journal, Vol. 14, Issue 12, pp. 22891-22906, 2014.
[11] A. Jain, M. Mittal, H. Verma, A. Rai, “Traffic Density Measurement based On-road Traffic Control using Ultrasonic Sensors and GSM Technology”, In the proceedings of the International Conference on Emerging Trends in Engineering and Technology, Nagpur, India, pp.778 – 786, 2013.
[12] M. Tideman, R. Bours, H. Li, T. Schulze, T. Nakano, “Integrated Simulation Toolkit for ADA System Development”, In the Proceedings of the FISITA 2012 World Automotive Congress, Lecture Notes in Electrical Engineering 200, Beijing, China, pp.23-33, 2013.
[13] P.J. Yauch, “Traffic Signal Control Equipment: State of the Art”, Transportation Research Board, National Research Council, Washington, pp. 23, 1990.