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Density Based Intelligent Traffic Light Control System Using High Range IR Sensors

R. Vigneshwaran, K. Venkatesan, A. Vinoth, J. Vasanth Vyasan, N. Sathishkumar

Abstract


In current traffic system most of the traffic lights controls are based on a „fixed timing‟ i.e., same time duration will be repeated even if the traffic density is minimum or maximum. In this paper the traffic light is controlled depending upon the traffic density is proposed. Here the traffic lights changes dynamically based on the traffic density by using pair of IR Sensor to continuously sense the density of traffic. The IR receiver output is given as the input of microcontroller in serial communication.The microcontroller will allocate the time slot according to the input of sensors, and then the CPU sends appropriate time to show on the seven segment display unit. When the allocated time is completed then the process will be shift into the next road. The same procedure it follows on each road. This system is designed by using PIC Microcontroller and three pairs of IR sensors on each lane. Here priority based operations by using the round robin algorithm is done. So, that each road will be cleared simultaneously. This system is mainly used to reduce the waiting time, avoid fuel wastage, and also manage the traffic load at the intersection adaptively, so that the traffic can be avoided.

Keywords


IR (Infrared) Sensor, PIC Microcontroller, Seven Segment Display

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References


Amrita Rai and Govind Singh Patel, “Multiple Traffic Control Using Wireless Sensor and Density Measuring Camera”, Sensors & Transducers Journal Vol. 94, Issue 7, July 2008, pp. 126-132

“Automatic Traffic Control System”. SMEU Astana Solutions Automatic Traffic Control System.htm

CihanKarakuzu, “Fuzzy logic based smart traffic light simulator design and hardware implementation”. Kocaeli University, Engineering Faculty, Electronics & Tell. Eng. Department, 41070 VezirogluYerleskesi, Izmit-Kocaeli, Turkey

Dinesh Rotake, Prof.SwapniliKarmore, “Intelligent traffic signal control system using embedded system”, Department of Electronics Engineering, G. H. Raisoni College of Engineering, Nagpur.

Kok, Khiang Tan and Marzuki, “Intelligent Traffic Lights Control by Fuzzy Logic”. Malaysian Journal of Computer Science

Marco Wiering. “Intelligent Traffic Light Control”. Institute of information and computing sciences, Utrecht University

NadhirMessai, Philippe Thomas, Dimitri Lefebvre and Abdellah El Moudni, “Neural networks for local monitoring of traffic magnetic sensors Control” Engineering Practice, Volume 13, Issue 1, January 2005.

PromilaSinhmar, “Intelligent traffic light and density control using IR sensors and microcontroller”, RawalInstitute of Engineering and Technology Zakopur, Faridabad.

Srinivasan, D., Choy, M.C. and Cheu, R.L., “Neural Networks for Real-Time Traffic Signal Control”, ITS (7), No. 3, September 2006, pp. 261-272.

V. Jain, A. Sharma, and L. Subramanian. “Road traffic congestion inThe developing world”. In ACM DEV, 2011

V. Kastrinaki, M. Zervakis, K. Kalaitzakis, “A survey of video processingtechniques for traffic applications”, Image Vis. Comput. 21, 359–381, 2003.

W. Wen & C. L. Yang. “A dynamic and automatic traffic light control system for solving the road congestion problem”.P89V51RD2 specification sheet. “Microcontroller with 64K Bytes Flash Memory”.


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