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master's thesis
Analiza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka
Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences, 2018. urn:nbn:hr:119:716383
Tišljarić, Leo
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

Tišljarić, L. (2018). Analiza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka (Master's thesis). Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:119:716383

Tišljarić, Leo. "Analiza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka." Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2018. https://urn.nsk.hr/urn:nbn:hr:119:716383

Tišljarić, Leo. "Analiza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka." Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2018. https://urn.nsk.hr/urn:nbn:hr:119:716383

Tišljarić, L. (2018). 'Analiza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka', Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, accessed 07 September 2024, https://urn.nsk.hr/urn:nbn:hr:119:716383

Tišljarić L. Analiza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka [Master's thesis]. Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences; 2018 [cited 2024 September 07] Available at: https://urn.nsk.hr/urn:nbn:hr:119:716383

L. Tišljarić, "Analiza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka", Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:119:716383

Metadata
TitleAnaliza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka
Title (english)Analysis of Queues and Level of Service on Urban Roads Using Machine Learning Algorithms and NoSQL Database
AuthorLeo Tišljarić
MentorTonči Carić (mentor)
Committee memberSadko Mandžuka (predsjednik povjerenstva)
Committee memberMario Muštra (član povjerenstva)
Committee memberPero Škorput (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 country2018-07-17, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Traffic and Transport Technology
Intelligent Transport Systems and Logistics
Abstract
Traffic data is main starting point for estimating performance or proposing improvements for traffic system. Vehicle speed and control delay are main parameters in Level of service ase-sment for roads and intersections. In this thesis methods for collecting, storing and processing GPS data in order to estimate traffic parameters is proposed. Method for estimating queue length on intersections approaches is presented and machine learning algorithm is used for clustering intersections based on their values of measured performance indicators. For calcula-tions and results, GUI based Python application is developed using MongoDB NoSQL database for storing data and results. Application contains three main features: processing and storing data, calculations of performance measures for intersections and implementation of machine learning algorithm for clustering data.
Abstract (english)
Kvalitetni prometni podaci osnovna su polazišna točka prilikom procjene stanja prometnog sustava ili prijedloga mogućih poboljšanja. Brzina vozila i vrijeme provedeno čekajući na raskrižju osnovni su parametri za procjenu razine uslužnosti neke prometnice ili raskrižja. U ovom radu opisana je metoda prikupljanja i obrade GPS podataka u svrhu procjene osnovnih parametara za opisivanje stanja prometnog toka i razine uslužnosti za prometnice i raskrižja. Prikazana je metoda procjene duljine repova čekanja na semaforiziranim raskrižjima te je primijenjen algoritam strojnog učenja kako bi se grupirala raskrižja na temelju mjerenih mjera učinkovitosti. Za potrebu izračuna svih navedenih parametara izrađena je aplikacija korištenjem Python programskog jezika i MongoDB NoSQL baze podataka. Aplikacija sadrži tri glavne funkcionalnosti: predobrada podataka i unos u bazu podataka, izračun karakterističnih parametara raskrižja i algoritam strojnog učenja za grupiranje podataka.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:119:716383
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 on2018-07-18 12:13:17