State-of-art review of traffic signal control methods: challenges and opportunities
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Date
2020
Authors
Syed Shah Sultan Mohiuddin Qadri
Mahmut Ali Gökçe
Erdinc Oner
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH info@springer-sbm.com
Open Access Color
GOLD
Green Open Access
No
OpenAIRE Downloads
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Publicly Funded
No
Abstract
Introduction: Due to the menacing increase in the number of vehicles on a daily basis abating road congestion is becoming a key challenge these years. To cope-up with the prevailing traffic scenarios and to meet the ever-increasing demand for traffic the urban transportation system needs effective solution methodologies. Changes made in the urban infrastructure will take years sometimes may not even be feasible. For this reason traffic signal timing (TST) optimization is one of the fastest and most economical ways to curtail congestion at the intersections and improve traffic flow in the urban network. Purpose: Researchers have been working on using a variety of approaches along with the exploitation of technology to improve TST. This article is intended to analyze the recent literature published between January 2015 and January 2020 for the computational intelligence (CI) based simulation approaches and CI-based approaches for optimizing TST and Traffic Signal Control (TSC) systems provide insights research gaps and possible directions for future work for researchers interested in the field. Methods: In analyzing the complex dynamic behavior of traffic streams simulation tools have a prominent place. Nowadays microsimulation tools are frequently used in TST related researches. For this reason a critical review of some of the widely used microsimulation packages is provided in this paper. Conclusion: Our review also shows that approximately 77% of the papers included utilizes a microsimulation tool in some form. Therefore it seems useful to include a review categorization and comparison of the most commonly used microsimulation tools for future work. We conclude by providing insights into the future of research in these areas. © 2020 Elsevier B.V. All rights reserved.
Description
Keywords
Computational Intelligence, Microsimulation, Traffic Signal Control, Traffic Signal Timing Optimization, Urban Traffic, Intelligent Computing, Street Traffic Control, Traffic Congestion, Urban Transportation, Complex Dynamic Behavior, Effective Solution, Number Of Vehicles, Simulation Approach, Traffic Signal Control, Traffic Signal Timings, Urban Infrastructure, Urban Transportation Systems, Traffic Signals, Intelligent computing, Street traffic control, Traffic congestion, Urban transportation, Complex dynamic behavior, Effective solution, Number of vehicles, Simulation approach, Traffic signal control, Traffic signal timings, Urban infrastructure, Urban transportation systems, Traffic signals, Computational intelligence, TA1001-1280, Traffic signal control, Urban traffic, Transportation engineering, Traffic signal timing optimization, Microsimulation, Transportation and communications, HE1-9990
Fields of Science
05 social sciences, 02 engineering and technology, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
142
Source
European Transport Research Review
Volume
12
Issue
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CrossRef : 4
Scopus : 186
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