Madrigal Arteaga, Victor Manuel und Pérez Cruz, José Roberto und Hurtado-Beltrán, Antonio und 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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Offizielle URL: https://www.mdpi.com/2076-3417/12/12/6024
Kurzfassung
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.
elib-URL des Eintrags: | https://elib.dlr.de/187141/ | ||||||||||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||
Titel: | Efficient Intersection Management Based on an Adaptive Fuzzy-Logic Traffic Signal | ||||||||||||||||||||
Autoren: |
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Datum: | 14 Juni 2022 | ||||||||||||||||||||
Erschienen in: | Applied Sciences | ||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||
Gold Open Access: | Ja | ||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||
Band: | 12 | ||||||||||||||||||||
DOI: | 10.3390/app12126024 | ||||||||||||||||||||
Verlag: | Multidisciplinary Digital Publishing Institute (MDPI) | ||||||||||||||||||||
Name der Reihe: | Transportation and Future Mobility | ||||||||||||||||||||
ISSN: | 2076-3417 | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | adaptive traffic signal; fuzzy logic; Webster method; microsimulation | ||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||
HGF - Programm: | Verkehr | ||||||||||||||||||||
HGF - Programmthema: | Straßenverkehr | ||||||||||||||||||||
DLR - Schwerpunkt: | Verkehr | ||||||||||||||||||||
DLR - Forschungsgebiet: | V ST Straßenverkehr | ||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | V - KoKoVI - Koordinierter kooperativer Verkehr mit verteilter, lernender Intelligenz | ||||||||||||||||||||
Standort: | Berlin-Adlershof | ||||||||||||||||||||
Institute & Einrichtungen: | Institut für Verkehrssystemtechnik > Kooperative Systeme, BA | ||||||||||||||||||||
Hinterlegt von: | Madrigal, Victor | ||||||||||||||||||||
Hinterlegt am: | 04 Jul 2022 09:35 | ||||||||||||||||||||
Letzte Änderung: | 18 Jul 2022 08:28 |
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