Developing a fuzzy-based decision-making procedure for traffic control in expressway congestion management

Trinh Dinh Toan, Yiik Diew Wong, Soi Hoi Lam, Meng Meng

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Abstract

This paper presents part of a multi-stage fuzzy logic controller (MS-FLC) that is developed for traffic control in congestion management on expressways. The decision-making process of traffic control for expressway congestion management using the MS-FLC consists of three tasks: (1) evaluation of current traffic congestion; (2) prediction of traffic congestion tendency; and (3) recommendation of control strategies and control actions to alleviate the congestion. This paper presents the 3rd stage of the MS-FLC that develops a fuzzy-based decision-making procedure (FDMP) for management of recurring and non-recurring congestion. Using fuzzy rules, the FDMP evaluates the current and anticipated traffic data and incident information to recommend control strategies at the strategic level, and control actions at the operational level. Results from this research show that: (i) the FDMP offers a comprehensive procedure in deriving control strategies and actions; (ii) FDMP control actions are derived from a systematic decision-making logic where the design of control rules is consistently oriented toward achieving desirable control objectives; (iii) the FDMP targets a proper balance in congestion management between the mainline and the ramp using compromise rule design; (iv) the FDMP facilitates using various forms of available traffic and incident data on an extended expressway segment to derive at control actions, making the system-wide gains possible; and (v) the FDMP could be applied for management of both recurring and non-recurring congestion.

Original languageEnglish
Article number127899
JournalPhysica A: Statistical Mechanics and its Applications
Volume604
Early online date14 Jul 2022
DOIs
Publication statusPublished - 15 Oct 2022

Bibliographical note

Funding Information:
The authors would like to gratefully acknowledge the Nanyang Technological University and Land Transport Authority of Singapore for provision of data and materials used in this research.

Keywords

  • Congestion management
  • Decision making
  • Fuzzy logic
  • Fuzzy rule base
  • Ramp metering
  • Traffic control

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability

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