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Efficient Intersection Management Based on an Adaptive Fuzzy-Logic Traffic Signal

Madrigal Arteaga, Victor Manuel and Pérez Cruz, José Roberto and Hurtado-Beltrán, Antonio and Trumpold, Jan (2022) Efficient Intersection Management Based on an Adaptive Fuzzy-Logic Traffic Signal. Applied Sciences, 12 (12). Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/app12126024. ISSN 2076-3417.

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Official URL: https://www.mdpi.com/2076-3417/12/12/6024

Abstract

Traffic signals may generate bottlenecks due to an unfair timing balance. Facing this problem, adaptive traffic signal controllers have been proposed to compute the phase durations according to conditions monitored from on-road sensors. However, high hardware requirements, as well as complex setups, make the majority of these approaches infeasible for most cities. This paper proposes an adaptive traffic signal fuzzy-logic controller which uses the flow rate, retrieved from simple traffic counters, as a unique input requirement. The controller dynamically computes the cycle duration according to the arrival flow rates, executing a fuzzy inference system guided by the reasoning: the higher the traffic flow, the longer the cycle length. The computed cycle is split into different phases proportionally to the arrival flow rates according to Webster’s method for signalization. Consequently, the controller only requires determining minimum/maximum flow rates and cycle lengths to establish if–then mappings, allowing the reduction of technical requirements and computational overhead. The controller was tested through a microsimulation model of a real isolated intersection, which was calibrated with data collected from a six-month traffic study. Results revealed that the proposed controller with fewer input requirements and lower computational costs has a competitive performance compared to the best and most used approaches, being a feasible solution for many cities.

Item URL in elib:https://elib.dlr.de/187141/
Document Type:Article
Title:Efficient Intersection Management Based on an Adaptive Fuzzy-Logic Traffic Signal
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Madrigal Arteaga, Victor ManuelVictor.MadrigalArteaga (at) dlr.dehttps://orcid.org/0000-0003-4724-9092
Pérez Cruz, José Robertojrpc (at) inaoep.mxhttps://orcid.org/0000-0002-2096-1453
Hurtado-Beltrán, Antonioantonio.hurtado (at) umich.mxhttps://orcid.org/0000-0001-9080-6910
Trumpold, JanJan.Trumpold (at) dlr.dehttps://orcid.org/0000-0001-6032-0709
Date:14 June 2022
Journal or Publication Title:Applied Sciences
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:12
DOI:10.3390/app12126024
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Transportation and Future Mobility
ISSN:2076-3417
Status:Published
Keywords:adaptive traffic signal; fuzzy logic; Webster method; microsimulation
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - KoKoVI - Koordinierter kooperativer Verkehr mit verteilter, lernender Intelligenz
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems > Cooperative Systems, BA
Deposited By: Madrigal, Victor
Deposited On:04 Jul 2022 09:35
Last Modified:18 Jul 2022 08:28

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