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      Traffic Control Prediction Design Based on Fuzzy Logic and Lyapunov Approaches to Improve the Performance of Road Intersection

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      Processes
      MDPI AG

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          Abstract

          Due to the increasing use of private cars for urbanization and urban transport, the travel time of urban transportation is increasing. People spend a lot of time in the streets, and the queue length of waiting increases accordingly; this has direct effects on fuel consumption too. Traffic flow forecasts and traffic light schedules were studied separately in the urban traffic system. This paper presents a new stable TS (Takagi–Sugeno) fuzzy controller for urban traffic. The state-space dynamics are utilized to formulate both the vehicle’s average waiting time at an isolated intersection and the length of queues. A fuzzy intelligent controller is designed for light control based upon the length of the queue, and eventually, the system’s stability is proved using the Lyapunov theorem. Moreover, the input variables are the length of queue and number of input or output vehicles from each lane. The simulation results describe the appearance of the proposed controller. An illustrative example is also given to show the proposed method’s effectiveness; the suggested method is more efficient than both the conventional fuzzy traffic controllers and the fixed time controller.

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          Most cited references40

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          Outline of a New Approach to the Analysis of Complex Systems and Decision Processes

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            Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control

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              A Fuzzy Logic Controller for a Trafc Junction

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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                PROCCO
                Processes
                Processes
                MDPI AG
                2227-9717
                December 2021
                December 07 2021
                : 9
                : 12
                : 2205
                Article
                10.3390/pr9122205
                f3328965-41db-4014-8a3b-293e85a1d505
                © 2021

                https://creativecommons.org/licenses/by/4.0/

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