Abstract
Fuzzy logic can be used effectively to deal with uncertainty in decision-making processes. Fuzzy control is based on the fuzzy set theory proposed by Zadeh [1, 2, 3]. There are three major ways to design fuzzy controllers. In the first method, the controller tries to emulate a human-like control action by transforming linguistic terms into fuzzy variables [4–7]. The second method is to develop heuristic based fuzzy controllers. In the third method, the traffic network is represented as a fuzzy system and a control is designed by analyzing the fuzzy model. In this paper, we employ the second method.
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References
Zadeh, L. A., Fuzzy Sets, Information Control, 8(3)( 1965)338–353.
Zadeh, L. A., The Role of Fuzzy Logic in the Management of Uncertainty in Expert Systems, Fuzzy Sets and Systems, 11 (1985) 199 – 227.
Zadeh, L. A., The Concept of Linguistic Variable and its Application to Approximate Reasoning - I, II, III, Information Sciences, 8(1975) 199–249, 8(1975) 301–357, 9 (1975) 43 – 80.
Mamdani, E. H., Advances in the Linguistic Synthesis of Fuzzy Controls, Int. J. Man-Machine Studies, 8 (1976) 699 – 678.
Mamdani, E. H., J. J. Ostergaard, and E. Lembessis, Use of Fuzzy Logic for Implementing Rule-Based Control of Industrial Processes, Wang, P. P. and Chang, S. K., eds. Advances in Fuzzy Sets Possibility Theory and Application, New York: Plenum(1983).
Kickert, W. J. M., and H. R.Van Nauta Lemke, Application of a Fuzzy Controller in a Warm Water Plant, Automatica, 12 (1976) 301 – 308.
Jain, P., and A. Rege, Survey of U.S. Applications of Fuzzy Logic:Hardware, Controls, Expert Systems, Patent Recognition, and Others, Agogino Engineering, 130 Wilding Ln., Oakland, CA, 94618(1987).
Lotan T. and H. N. Koutsopoulos, “Fuzzy Control and Approximate Reasoning Models for Route Choice in the Presence of Information”, Paper presented at the 73rd Annual TRB Meeting, 1993.
Lotan T. and H. N. Koutsopoulos, “Approximate Reasoning Models for Route Choice in the Presence of Information”, Transportation and Traffic Theory, Proceedings of the 12th International Symposium on the Theory of Traffic Flow and Transportation, Berkeley, California, 21 – 23 July 1993.
Sasaki, T, and T. Akiyama,“ Traffic Control Process of Expressway by Fuzzy Logic”, Fuzzy Sets and Systems 26 165 – 178, 1988.
Chen, L. C., A. D. May, and D. M. Auslander, “ Freeway Ramp Control Using Fuzzy Set Theory for Inexact Reasoning”, Transpn. Res.-A, Vol. 24 A, No. 1., p. 15 – 25, 1990.
Mendel, Jerry M., ‘Fuzzy logic systems for engineering: a tutorial’, Proc. of the IEEE, vol. 83, No. 3, March 1995.
Klir, George J. and Folger, Tina A., Fuzzy Sets Uncertainty, and Information, Prentice Hall, 1988.
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© 1999 Springer-Verlag
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Kachroo, P., Özbay, K. (1999). Fuzzy Feedback Control for Dynamic Traffic Routing. In: Feedback Control Theory for Dynamic Traffic Assignment. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-0815-3_6
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DOI: https://doi.org/10.1007/978-1-4471-0815-3_6
Publisher Name: Springer, London
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