Analiza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka

Tišljarić, Leo

prikaz prve stranice dokumenta Analiza repova čekanja i razine uslužnosti urbanih prometnica korištenjem algoritama strojnog učenja i NoSQL baza podataka

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

Cite this document

APA 6th Edition

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

MLA 8th Edition

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

Chicago 17th Edition

Harvard

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 24 March 2025, https://urn.nsk.hr/urn:nbn:hr:119:716383

Vancouver

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 2025 March 24] Available at: https://urn.nsk.hr/urn:nbn:hr:119:716383

IEEE

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

Cite this item: https://urn.nsk.hr/urn:nbn:hr:119:716383

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Metadata

Title	Analiza 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
Author	Leo Tišljarić
Mentor	Tonči Carić (mentor)
Committee member	Sadko Mandžuka (predsjednik povjerenstva)
Committee member	Mario Muštra (član povjerenstva)
Committee member	Pero Škorput (član povjerenstva)
Granter	University of Zagreb Faculty of Transport and Traffic Sciences (Division of Intelligent Transport Systems and Logistics) (Department of Intelligent Transport Systems) Zagreb
Defense date and country	2018-07-17, 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)
Language	croatian
URN:NBN	urn:nbn:hr:119:716383
Study programme	Title: 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 resource	Text
File origin	Born digital
Access conditions	Open access
Terms of use
Repository	Faculty of Transport and Traffic Sciences
Created on	2018-07-18 12:13:17