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master's thesis
Analiza utjecaja meteoroloških prilika i stanja kolnika na poštivanje ograničenja brzine
Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences, 2024. urn:nbn:hr:119:127817
Batarilo, Zvonimir
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

Batarilo, Z. (2024). Analiza utjecaja meteoroloških prilika i stanja kolnika na poštivanje ograničenja brzine (Master's thesis). Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:119:127817

Batarilo, Zvonimir. "Analiza utjecaja meteoroloških prilika i stanja kolnika na poštivanje ograničenja brzine." Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2024. https://urn.nsk.hr/urn:nbn:hr:119:127817

Batarilo, Zvonimir. "Analiza utjecaja meteoroloških prilika i stanja kolnika na poštivanje ograničenja brzine." Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2024. https://urn.nsk.hr/urn:nbn:hr:119:127817

Batarilo, Z. (2024). 'Analiza utjecaja meteoroloških prilika i stanja kolnika na poštivanje ograničenja brzine', Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, accessed 13 January 2025, https://urn.nsk.hr/urn:nbn:hr:119:127817

Batarilo Z. Analiza utjecaja meteoroloških prilika i stanja kolnika na poštivanje ograničenja brzine [Master's thesis]. Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences; 2024 [cited 2025 January 13] Available at: https://urn.nsk.hr/urn:nbn:hr:119:127817

Z. Batarilo, "Analiza utjecaja meteoroloških prilika i stanja kolnika na poštivanje ograničenja brzine", Master's thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:119:127817

Metadata
TitleAnaliza utjecaja meteoroloških prilika i stanja kolnika na poštivanje ograničenja brzine
Title (english)Analysis of Meteorological and Road Conditions on Compliance with Speed Limits
AuthorZvonimir Batarilo
MentorMartin Gregurić (mentor)
Committee memberMiroslav Vujić (predsjednik povjerenstva)
Committee memberLuka Novačko (član povjerenstva)
Committee memberEdouard Ivanjko (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 country2024-09-25, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Traffic and Transport Technology
Intelligent Transport Systems and Logistics
Abstract
Znanost o podacima (engl. Data science) je računalna disciplina koja se bavi problemom izvlačenja znanja iz strukturiranih i nestrukturiranih podataka, uključujući velike skupove podataka. Jedna takva velika skupina podataka nudi uvid o brzinama i kategorijama vozila koja se kreću dionicom Zagreb-Karlovac na autocesti A1 u rasponu od 3 godine od 2018. godine do 2020. godine. Također, za isti period zabilježeni su i meteorološki podaci za tu istu dionicu. Podaci sadržavaju informacije kao što su: vrsta i intenzitet oborina; temperatura zraka i kolnika, točke ledišta kolnika; vidljivosti; debljini vodenog sloja; maksimalnoj brzini vjetra; opasnosti od poledice i stanju povrtine kolnika. Svaka ta meteorološka značajka i značajka o stanju kolnika utječe na brzinu vožnje motornih vozila na promatranoj dionici. Unutar diplomskog rada vizualizirat će se ti utjecaji kako bi se utvrdile one značajke koje najviše utječu na brzinu motornih vozila. Stvorit će se model korištenjem metoda strojnog učenja, odabir meteoroloških značajki i značajki stanja kolnika s najvećim utjecajem na brzinu vozila na autocesti. Zatim će se provesti analiza koja će dovesti u korelaciju poštivanje ograničenja brzine u odnosu na odabrane značajke. Rezultati će odgovarajuće vizualizirati i interpretirati u kontekstu mogućih intervencija u povećanju poštivanja ograničenja brzine u nepovoljnim prilikama.
Abstract (english)
Data science is a computational discipline that addresses the problem of extracting knowledge from structured and unstructured data, including large datasets. One such large dataset provides insight into the speeds and categories of vehicles traveling the Zagreb-Karlovac section of the A1 highway over a period of 3 years, from 2018 to 2020. Additionally, meteorological data for the same section were recorded during the same period. The data include information such as: type and intensity of precipitation; air and road surface temperatures; freezing points of the road surface; visibility; thickness of the water layer; maximum wind speed; risk of ice formation, and the condition of the road surface. Each of these meteorological features, as well as the road condition features, affects the speed of vehicles on the observed section. Within this thesis, these influences will be visualized to determine which features have the greatest impact on vehicle speed. A model will be created using machine learning methods to select the meteorological and road condition features with the greatest influence on vehicle speed on the highway. Following this, an analysis will be conducted to correlate speed limit compliance with the selected features. The results will be appropriately visualized and interpreted in the context of potential interventions to increase compliance with speed limits under adverse conditions.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:119:127817
Study programmeTitle: Intelligent Transportation Systems and Logistics
Study programme type: university
Study level: graduate
Academic / professional title: sveučilišni/a magistar/magistra inženjer/inženjerka prometa (sveučilišni/a magistar/magistra inženjer/inženjerka prometa)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-12-05 12:46:11