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An intelligent control system for traffic lights with simulation-based evaluation
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.ORCID iD: 0000-0002-1375-9054
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
2017 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 58, 24-33 p.Article in journal (Refereed) Published
Abstract [en]

This paper introduces an intelligent control system for traffic signal applications, called Fuzzy Intelligent Traffic Signal (FITS) control. It provides a convenient and economic approach to improve existing traffic light infrastructure. The control system is programmed on an intermediate hardware device capable of receiving messages from signal controller hardware as well as overriding traffic light indications during real-time operations. Signal control and optimization toolboxes are integrated into the embedded software in the FITS hardware device. A fuzzy logic based control has been implemented in FITS. In order to evaluate the effects of FITS system, this study attempts to develop a computational framework to evaluate FITS system using microscopic traffic simulation. A case study is carried out, comparing different commonly used signal control strategies with the FITS control approach. The simulation results show that the control system has the potential to improve traffic mobility, compared to all of the tested signal control strategies, due to its ability in generating flexible phase structures and making intelligent timing decisions. In addition, the effects of detector malfunction are also investigated in this study. The experiment results show that FITS exhibits superior performance than several other controllers when a few detectors are out-of-order due to its self-diagnostics feature. © 2016 Elsevier Ltd

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 58, 24-33 p.
Keyword [en]
Adaptive traffic signal control, Embedded system, Fuzzy control, Real-time traffic simulation, Adaptive control systems, Computation theory, Control systems, Controllers, Embedded systems, Fuzzy logic, Hardware, Intelligent control, Reconfigurable hardware, Street traffic control, Computational framework, Fuzzy logic based control, Intelligent traffics, Microscopic traffic simulation, Real time traffics, Real-time operation, Signal control strategy, Traffic signals
National Category
Civil Engineering
URN: urn:nbn:se:kth:diva-195121DOI: 10.1016/j.conengprac.2016.09.009ISI: 000390073900003ScopusID: 2-s2.0-84990875234OAI: diva2:1048295

Correspondence Address: Ma, X.; System Simulation & Control (S2CLab), Department of Transport Science, KTH Royal Institute of Technology, Teknikringen 10, Sweden; email: QC 20161121

Available from: 2016-11-21 Created: 2016-11-02 Last updated: 2017-01-16Bibliographically approved

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