An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using Sumo Traffic Simulator
Loading...
Date
2021
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Open Access Color
GOLD
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
In the past, the Webster optimal cycle time formula was limited to calculate the optimal cycle from historical data for fixed-time traffic signal control. This paper focuses on the design of an adaptive traffic signal control based on fuzzy logic with Webster and modified Webster's formula. These formulas are used to calculate the optimal cycle time depending on the current traffic situation which applying in the next cycle. The alternation of the traffic condition between two successive cycles is monitored and handled through the fuzzy logic system to compensate the fluctuation. The obtained optimal cycle time is used to determine adaptively the effective phase green times i.e. is used to determine adaptively the maximum allowable extension limit of the green phase in the next cycle. The SUMO traffic simulator is used to compare the results of the proposed adaptive control methods with fuzzy logic-based traffic control, and fixed-time Webster and modified Webster-based traffic control methods. The proposed methods are tested on an isolated intersection. In this study, real field-collected data obtained from three, four, and five approaches intersections in Kilis/Turkey are used to test the performance of the proposed methods. In addition, to examine the efficiency of the proposed techniques at heavy demands, the arbitrary demands are generated by SUMO for a four approaches intersection. The obtained simulation results indicate that the proposed methods overperform the fixed time and fuzzy logic-based traffic control methods in terms of average vehicular delay, speed, and travel time.
Description
ORCID
Keywords
Traffic Control, Fuzzy Logic, Mathematical Model, Adaptation Models, Optimization, Heuristic Algorithms, Vehicle Dynamics, Adaptive Traffic Control, Fixed-Time Traffic Control, Fuzzy Logic Control, Modified Webster's Formula, Sumo Simulator, Webster's Formula, Intersections, System, Artificial intelligence, fuzzy logic control, Social Sciences, Transportation, Traffic Signal Control, Control (management), Real-time computing, Traffic signal, Engineering, SUMO Simulator, modified Webster’s formula, Control theory (sociology), Fuzzy Logic Control, SUMO simulator, Webster's Formula, Adaptive Traffic Control, Fixed-Time Traffic Control, Modified Webster's Formula, Understanding Attitudes Towards Public Transport and Private Car, Traffic Flow Prediction and Forecasting, Building and Construction, Computer science, Webster’s formula, TK1-9971, Programming language, Fuzzy logic, Aerospace engineering, fixed-time traffic control, Signal timing, Fuzzy control system, Control and Systems Engineering, SIGNAL (programming language), Physical Sciences, Electrical engineering. Electronics. Nuclear engineering, Intersection (aeronautics), Modeling and Control of Traffic Flow Systems, Simulation, Adaptive traffic control
Turkish CoHE Thesis Center URL
Fields of Science
02 engineering and technology, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, 05 social sciences
Citation
WoS Q
Q2
Scopus Q
Q1

OpenCitations Citation Count
27
Source
IEEE ACCESS
Volume
9
Issue
Start Page
102985
End Page
102997
PlumX Metrics
Citations
Scopus : 43
Captures
Mendeley Readers : 66
Google Scholar™

OpenAlex FWCI
4.11782018
Sustainable Development Goals
11
SUSTAINABLE CITIES AND COMMUNITIES


