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Hierarchical fuzzy logic traffic controller for urban signalized intersections

Zuyuan Yang, Xiyue Huang, Changhai Du, Mingxia Tang, Yang Fang-xun

Open publisher page 7 citations

Abstract

Dynamic signal control is considered an effective measure to deal with urban traffic congestion by increasing intersection capacity and decreasing delays at the same time. A hierarchical fuzzy logic controller for urban signalized intersections is developed in this paper. The controller is designed to be responsive to real-time traffic intensities. Vehicle detectors are placed upstream of the intersection on each approach to measure approach flows and estimate queues. The data is used to decide how much to extend the current green phase. These decisions are made by using a hierarchical fuzzy logic procedure. In the first stage, detected approach traffic flows and the vehicles in the queue are used to estimate relative traffic intensities in the competing approaches. These traffic intensities are then used in the second stage to determine the extension of the current green phase. The performance of this controller is validated in a four-phase signalized intersection by a simulation experiment. The result shows that this control method outperforms the conventional single-stage fuzzy logic controller, especially in the case of heavy traffic flows.

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What this paper is about

Dynamic signal control is considered an effective measure to deal with urban traffic congestion by increasing intersection capacity and decreasing delays at the same time. A hierarchical fuzzy logic controller for urban signalized intersections is developed in this paper. The controller is designed to be responsive to real-time traffic intensities. Vehicle detectors are placed upstream of the intersection on each approach to measure approach flows and estimate queues. The data is used to decide how much to extend the current green phase. These decisions are made by using a hierarchical fuzzy logic procedure. In the first stage, detected approach traffic flows and the vehicles in the queue are used to estimate relative traffic intensities in the competing approaches. These traffic intensities are then used in the second stage to determine the extension of the current green phase. The performance of this controller is validated in a four-phase signalized intersection by a simulation experiment. The result shows that this control method outperforms the conventional single-stage fuzzy logic controller, especially in the case of heavy traffic flows.

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Available abstract

Dynamic signal control is considered an effective measure to deal with urban traffic congestion by increasing intersection capacity and decreasing delays at the same time. A hierarchical fuzzy logic controller for urban signalized intersections is developed in this paper. The controller is designed to be responsive to real-time traffic intensities. Vehicle detectors are placed upstream of the intersection on each approach to measure approach flows and estimate queues. The data is used to decide how much to extend the current green phase. These decisions are made by using a hierarchical fuzzy logic procedure. In the first stage, detected approach traffic flows and the vehicles in the queue are used to estimate relative traffic intensities in the competing approaches. These traffic intensities are then used in the second stage to determine the extension of the current green phase. The performance of this controller is validated in a four-phase signalized intersection by a simulation experiment. The result shows that this control method outperforms the conventional single-stage fuzzy logic controller, especially in the case of heavy traffic flows.

Key concepts: Intersection (aeronautics), Fuzzy logic, Queue, Controller (irrigation), Computer science, Measure (data warehouse), Traffic flow (computer networking), Control theory (sociology)

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