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Fuzzy System-Based Solutions for Traffic Control in Freeway Networks Toward Sustainable Improvement

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Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1602))

Abstract

In the scientific community, the topic of traffic control for promoting sustainable transportation in freeway networks is a relatively new field of research that is becoming increasingly relevant. Sustainability is a critical factor in the design and operation of mobility and traffic systems, which impacts the development of freeway traffic control strategies. According to sustainable notions, freeway traffic controllers should be designed to maximize road capacity, minimize vehicle travel delays, and reduce pollution emissions, accidents, and fuel consumption. The problem is full of uncertainty, there is no way to model the whole system analytically, thus a fuzzy modeling approach seems to be not only adequate but necessary. In this study, a Fuzzy Cognitive Map based model (FCM) and a connected simple Fuzzy Inference System (FIS) are presented, as the tools to analyze freeway traffic data with the goal of traffic flow modeling at a macroscopic level, in order to address congestion-related issues as the core of the sustainability improvement strategies. Besides presenting a framework of Fuzzy system-based controllers in freeway traffic, the results of this work indicated that FIS and FCM are capable of realizing traffic control strategies involving the implementation of ramp management policies, controlling vehicle movement within the freeway by mainstream control, and routing vehicles along alternative paths via the execution of suitable route guidance strategy.

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Acknowledgements

The authors gratefully acknowledge Gergely Mikulai and Hungarian national toll payment services for their work on providing the original dataset. László T. Kóczy is supported by NKFIH K124055 grants.

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Authors and Affiliations

  1. Department of Information Technology, Szechenyi Istvan University, Gyor, Hungary

    Mehran Amini, Miklos F. Hatwagner & Laszlo T. Koczy

  2. Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary

    Mehran Amini, Miklos F. Hatwagner & Laszlo T. Koczy

Authors
  1. Mehran Amini
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  2. Miklos F. Hatwagner
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  3. Laszlo T. Koczy
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Corresponding author

Correspondence to Mehran Amini .

Editor information

Editors and Affiliations

  1. University of Milano-Bicocca, Milan, Italy

    Davide Ciucci

  2. University of Oviedo, Oviedo, Spain

    Inés Couso

  3. University of Cádiz, Cádiz, Spain

    Jesús Medina

  4. University of Warsaw, Warsaw, Poland

    Dominik Ślęzak

  5. University of Perugia, Perugia, Italy

    Davide Petturiti

  6. Sorbonne Université, Paris, France

    Bernadette Bouchon-Meunier

  7. Iona College, New Rochelle, NY, USA

    Ronald R. Yager

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Amini, M., Hatwagner, M.F., Koczy, L.T. (2022). Fuzzy System-Based Solutions for Traffic Control in Freeway Networks Toward Sustainable Improvement. In: Ciucci, D., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2022. Communications in Computer and Information Science, vol 1602. Springer, Cham. https://doi.org/10.1007/978-3-031-08974-9_23

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  • DOI: https://doi.org/10.1007/978-3-031-08974-9_23

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  • Online ISBN: 978-3-031-08974-9

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