International Journal of Innovative Research in Engineering and Management
Year: 2019, Volume: 6, Issue: 4
First page : ( 33) Last page : ( 37)
Online ISSN : 2350-0557.
DOI: 10.21276/ijirem.2019.6.4.2 |
DOI URL: https://doi.org/10.21276/ijirem.2019.6.4.2
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
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Elda Maraj , Shkelqim Kuka, Zhifka Muka
The purpose of this paper is to develop a fuzzy logic model for traffic system. This model is used to overcome the problem of traffic congestion in cities. Consequently, travelling time, fuel consumption and pollution can reduce. Moreover, traffic flow prediction helps the transport users to plan their time of travel and also in selecting the travelling path depending on the predicted information. In this paper, we used density of vehicles variable to design a system which uses the green signal depending on the number of vehicles in that particular line. Here fuzzy logic toolbox of MATLAB is used. The fuzzy sets and membership functions are chosen in an appropriate manner.
[1] Javed Alam and Dr. M.K. Pandey “Development of Traffic Light Control System for Emergency Vehicle Using Fuzzy Logic” International Conference on Artificial Intelligence and Soft Computing, IIT-BHU Varanasi, India 7-9 December2012.
[2] Li, H, P. D. Prevedouros, and L. Zhang. “Signal Control for Oversaturated Intersections Using Fuzzy Logic” Submitted for consideration for presentation at the 2005 Annual Meeting of the TRB and publication in the Transportation Research Record.
[3] L.X. Wang, “A Course in Fuzzy Systems and Control”, International Edition, Prentice-Hall International Inc., 1997, pp.1-126. .
[4] R. Naja and R. Matta, “Fuzzy Logic Ticket Rate Predictor for Congestion Control in Vehicular Networks, Wireless Personal Communications”, Volume 79, Issue 3, pp. 1837-1858, December 2014.
[5] Sarkar, A. 2012. Application of Fuzzy Logic in Transport Planning. International Journal on Soft Computing. 1-21.
[6] Stepe, V. 1999. Fuzzy Logic Systems for Transportation Engineering: The State of the Art. Transportation Research Part A: Policy and Practice. 337-364.
[7] Zadeh, L.A.: Fuzzy logic, neural networks, and soft computing. Communications of the ACM. 37, 77-84 (1994).
[8] Zadeh, L.A.: Is there a need for fuzzy logic? Information sciences. 178, 2751-2779 (2008) .
[9] Gupta, M.: Forty-five years of fuzzy sets and fuzzy logic – A tribute to Professor Lotfi A. Zadeh (the father of fuzzy logic). Scientia Iranica. 18, 685-690 (2011) .
[10] Priyanka Shevade, Yajuta Kajale, Nimisha Mathew, Amrapali Kharat, Dr.Ravindra Duche:“Traffic System using Fuzzy Logic”, International Journal of Scientific & Engineering Research Volume 9, Issue 3, March-2018.
Department of Mathematic Engineering, Mathematical Engineering and Physics Engineering Faculty, Polytechnic University of Tirana, Albania e.maraj@fimif.edu.al
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