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A Prototype of Density-Based Intelligent Traffic Light Control System Using Image Processing Technique and Arduino Microcontroller in Lab VIEW Environment

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Advances in Electrical Control and Signal Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 665))

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Abstract

Nowadays traffic congestion is a serious issue associated with transportation, the backbone of the economy of a city. Because of the rise in population and number of vehicles on a road, traffic jam is very common all over the world. Congestion not only rises pollution, stress, frustration but also wastes money, fuel. Another serious cause of congestion is the delay in red light at a junction. In our work, we proposed a technique to optimize the red light ON duration of traffic light controller depending on traffic. Regulation of road traffic at each junction in a city is the main aim of our work. Our system measures traffic density at different lanes at a junction and accordingly changes the time delay of red light. This system controls the traffic light by image processing using MATLAB. Cameras are installed for each lane to capture the image, which is analyzed by Lab VIEW to detect congestion on a particular lane and according to congestion, the green light of each lane is controlled from that lane using Arduino microcontroller.

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References

  1. Ki, Y., Baik, D.: Model for accurate speed measurement using double-loop detectors. IEEE Trans. Veh. Technol. 55(4), 1094–1101 (2006)

    Article  Google Scholar 

  2. Deekshitha., Disha, D., Malavika, Soumya.: Traffic monitoring system using IR sensors. Int. J. Adv. Res. Ideas Innovations Technol. 3(3), 1045–1057 (2017)

    Google Scholar 

  3. Haoui, A., Kavaler, R., Varaiya, P.: Wireless magnetic sensors for traffic surveillance. Transp. Res. Part C: Emerg. Technol. 16(3), 294–306 (2008)

    Google Scholar 

  4. Zhang, J., Lu, Y., Lu, Z., Liu, C., Sun, G., Li, Z.: A new smart traffic monitoring method using embedded cement-based piezoelectric sensors. Smart Mater. Struct. IOP Sci. 24(2), 1–8 (2015)

    Google Scholar 

  5. Barbagli, B., Manes, G., Facchini, R., Manes, A.: Acoustic sensor network for vehicle traffic monitoring. In: International Conference on Advances in Vehicular Systems, Technologies and Applications, VEHICULAR-2012, pp. 1–6 (2012)

    Google Scholar 

  6. Beymer, D., McLauchlan, P., Coifman, B., Malik, J.: A real-time computer vision system for measuring traffic parameters. In: IEEE Conference on Computer Vision and Pattern Recognition, p. 495–501 (1997)

    Google Scholar 

  7. Fathy, M., Siyal, M.Y.: An image detection technique based on morphological edge detection and background differencing for real time traffic analysis. Pattern Recogn. Lett. 16, 1321–1330 (1995)

    Article  Google Scholar 

  8. Ferrier, N.J., Rowe, S.M., Blake, A.: Real-time traffic monitoring. In: Proceedings of the Second IEEE Workshop on Applications of Computer Vision, pp. 81–88 (1994)

    Google Scholar 

  9. Cucchiara, R., Piccardi, M., Mello, P.: Image analysis and rule-based reasoning for a traffic monitoring system. IEEE Trans. Intell. Transp. Syst. 1(2), 119–130 (2000)

    Article  Google Scholar 

  10. Sehgal, V.K., Dhope, S., Goel, P.: An embedded platform for intelligent traffic control. In: UKSim Fourth European Modeling Symposium on Computer Modeling and Simulation, IEEE Computer Society, pp. 541–545 (2010)

    Google Scholar 

  11. Chavan, S.S., Deshpande, R.S., Rana, J.G.: Design of intelligent traffic light controller using embedded system. In: Second International Conference on Emerging Trends in Engineering and Technology, ICETET-09, IEEE Computer Society, pp. 1086–1091 (2009)

    Google Scholar 

  12. Maram, Y.B., Azzedine, B.: Efficient traffic congestion detection protocol for next generation VANETs. In: ICC. IEEE, pp. 3764–3768 (2013)

    Google Scholar 

  13. Fernando, T.S., Mercedes, V.V., Cristina, S.M.: A cooperative approach to traffic congestion detection with complex event processing and VANET. IEEE Trans. Intell. Transp. Syst. 13(2), 914–928 (2012)

    Article  Google Scholar 

  14. Prajakta, D., Seng, L.W., Aniruddha, D., Jugdutt, S.: CARAVAN: congestion avoidance and route allocation using virtual agent negotiation. IEEE Trans. Intell. Transp. Syst. 14(3), 1197–1207 (2013)

    Article  Google Scholar 

  15. Azimirad, E., Pariz, N., Sistani, M.B.N.: A novel fuzzy model and control of single intersection at urban traffic network. IEEE Syst. J. 4(1), 107–111 (2010)

    Article  Google Scholar 

  16. Al okaishi, W., Atouf, I., Benrabh, M.: Real-time traffic light control system based on background updating and edge detection. In: International Conference on Wireless Technologies, Embedded and Intelligent Systems, IEEE Publication (2019) 1–5

    Google Scholar 

  17. Patela, V.K., Patel, M.N.: Development of intelligent traffic control system by implementing fuzzy-logic controller in lab view and measuring vehicle density by image processing tool in Lab VIEW. Am. Sci. Res. J. Eng. Technol. Sci. (ASRJETS). Global Soc. Sci. Res. Researchers 26(4), 406–417 (2016)

    Google Scholar 

  18. Prutha, A.: Morphological image processing approach of vehicle detection for real-time traffic analysis. Int. J. Eng. Res. Technol. (IJERT) 3(5) (2014)

    Google Scholar 

  19. Chintalacheruvu, N., MuthuKumar, V.: Video based vehicle detection and its application in Intelligent transportation systems. Sci. Res. J. Transp. Technol. 2, 305–314 (2012)

    Google Scholar 

  20. Suhweil, Y., Al Yaman, M.: Smart controlling for traffic light time. In: IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), pp. 1–5 (2017)

    Google Scholar 

  21. Hasan, M.M., Saha, G., Hoque, A., Majumder, M.B.: Smart traffic control system with application of image processing techniques. In: International Conference on Informatics, Electronics & Vision, pp. 1–4 (2014)

    Google Scholar 

  22. Uddin, M.S., Das, A.K., Taleb, M.A.: Real-time area based traffic density estimation by image processing for traffic signal control system: Bangladesh perspective. In: International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), pp. 1–5 (2015)

    Google Scholar 

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Correspondence to Anita Mohanty .

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Mohanty, A., Mohanty, S.K., Kumar, J. (2020). A Prototype of Density-Based Intelligent Traffic Light Control System Using Image Processing Technique and Arduino Microcontroller in Lab VIEW Environment. In: Pradhan, G., Morris, S., Nayak, N. (eds) Advances in Electrical Control and Signal Systems. Lecture Notes in Electrical Engineering, vol 665. Springer, Singapore. https://doi.org/10.1007/978-981-15-5262-5_56

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  • DOI: https://doi.org/10.1007/978-981-15-5262-5_56

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