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master's thesis
Adaptivno upravljanje izoliranim semaforiziranim raskrižjem primjenom neizrazite logike
Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences, 2020. urn:nbn:hr:119:585771
Vogel, Alan
University of Zagreb
Faculty of Transport and Traffic Sciences
Division of Intelligent Transport Systems and Logistics
Department of Intelligent Transport Systems

Institutional repository: Faculty of Transport and Traffic Sciences

Cite this document

Vogel, A. (2020). Adaptivno upravljanje izoliranim semaforiziranim raskrižjem primjenom neizrazite logike (Master's thesis). Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:119:585771

Vogel, Alan. "Adaptivno upravljanje izoliranim semaforiziranim raskrižjem primjenom neizrazite logike." Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2020. https://urn.nsk.hr/urn:nbn:hr:119:585771

Vogel, Alan. "Adaptivno upravljanje izoliranim semaforiziranim raskrižjem primjenom neizrazite logike." Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2020. https://urn.nsk.hr/urn:nbn:hr:119:585771

Vogel, A. (2020). 'Adaptivno upravljanje izoliranim semaforiziranim raskrižjem primjenom neizrazite logike', Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, accessed 14 March 2025, https://urn.nsk.hr/urn:nbn:hr:119:585771

Vogel A. Adaptivno upravljanje izoliranim semaforiziranim raskrižjem primjenom neizrazite logike [Master's thesis]. Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences; 2020 [cited 2025 March 14] Available at: https://urn.nsk.hr/urn:nbn:hr:119:585771

A. Vogel, "Adaptivno upravljanje izoliranim semaforiziranim raskrižjem primjenom neizrazite logike", Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:119:585771

Metadata
TitleAdaptivno upravljanje izoliranim semaforiziranim raskrižjem primjenom neizrazite logike
Title (english)Adaptive Control of Isolated Signalized Intersections using Fuzzy Logic
AuthorAlan Vogel
MentorEdouard Ivanjko (mentor)
MentorMartin Gregurić (komentor)
Committee memberHrvoje Gold (predsjednik povjerenstva)
Committee memberLuka Novačko (član povjerenstva)
Committee memberMiroslav Vujić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Transport and Traffic Sciences
(Division of Intelligent Transport Systems and Logistics)
(Department of Intelligent Transport Systems)
Zagreb
Defense date and country2020-09-24, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Traffic and Transport Technology
Intelligent Transport Systems and Logistics
Abstract
Cestovni promet se dinamički mijenja ovisno o vremenu, a to se najbolje može uočiti tijekom vršnog sata. U današnje vrijeme dolazi do promjena gradskih zona ovisno o gradnji ili obnovi starih objekata i migraciji stanovništva koje sve više dolazi živjeti u gradovima u potrazi za boljim prilika. Radi porasta potražnje korištenja transportnih usluga na gradskim cestama dolazi do sve većih problema prometnih zagušenja. Iz tog razloga potrebna su nova rješenja u vidu smanjivanja prometnih zagušenja, onečišćenja okoliša i poboljšanja postojeće prometne infrastrukture s obzirom na to da se gradske ulice više ne mogu proširiti. Iz tih razloga ciljevi ovoga rada su izrada algoritma za adaptivno upravljanje semaforiziranog raskrižja u cilju smanjenja duljine repa čekanja i broja zaustavljanja vozila na gradskim raskrižjima. Napravljeni algoritam ima četiri metode upravljanja i testiran je koristeći realne prikupljene podatke o broju vozila (prometna potražnja) na raskrižju, te je ispitano djelovanje algoritma u uvjetima gdje je prometna potražnja povećana, odnosno smanjena za 40%. Za potrebe ispitivanje algoritma upravljanja semaforiziranog raskrižja izraden je model raskrižja primjenom mikroskopskog simulatora PTV VISSIM u kojemu se vršila simulacija. Algoritam je izraden unutar programskog jezika Python preko kojeg su se pokretale simulacije i algoritmi, te se preko COM veze Python- VISSIM upravljalo semaforiziranim raskrižjem.
Abstract (english)
Road traffic changes dynamically during some periods, and it can be specialy noticed during peak hours. Nowadays, there can be changes in urban zones depending on the new construction or renovation of old facilities and the increased migration of the population coming to live in cities in search of better opportunities. Due to this problem of increasing traffic congestion on the city streets appears with the growing demand for transport services. For this reason, new solutions are needed for reducing traffic congestion, environmental pollution, and improving the existing transport infrastructure, given that the city streets can no longer be expanded. For these reasons, this thesis aims to present an adaptive traffic light controller to reduce the queue length and number of stop vehicles for traffic intersections. The algorithm has four types of control and was evaluated using real traffic data such as the number of vehicles (traffic demand), and the algorithm was tested on the different conditions where traffic demand was increased or decreased by 40% of the original traffic demand. An adaptive traffic signal controller was tested using a model of the isolated intersection in the microscopic simulator PTV VISSIM. The algorithm of an adaptive traffic light controller was created in the Python programming language, which was used for running and testing our simulations and four types of algorithms through the COM connection Python-VISSIM.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:119:585771
Study programmeTitle: Intelligent Transport Systems and Logistics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka prometa (magistar/magistra inženjer/inženjerka prometa)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-10-29 14:28:37