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master's thesis
Tehnike umjetne inteligencije u upravljanju autonomnim prometnim sredstvima
Split: University of Split, Faculty of Maritime Studies, 2024. urn:nbn:hr:164:001576
Marić, Nina
University of Split
Faculty of Maritime Studies
Department of nautical studies

Institutional repository: Repository - Faculty of Maritime Studies - Split

Cite this document

Marić, N. (2024). Tehnike umjetne inteligencije u upravljanju autonomnim prometnim sredstvima (Master's thesis). Split: University of Split, Faculty of Maritime Studies. Retrieved from https://urn.nsk.hr/urn:nbn:hr:164:001576

Marić, Nina. "Tehnike umjetne inteligencije u upravljanju autonomnim prometnim sredstvima." Master's thesis, University of Split, Faculty of Maritime Studies, 2024. https://urn.nsk.hr/urn:nbn:hr:164:001576

Marić, Nina. "Tehnike umjetne inteligencije u upravljanju autonomnim prometnim sredstvima." Master's thesis, University of Split, Faculty of Maritime Studies, 2024. https://urn.nsk.hr/urn:nbn:hr:164:001576

Marić, N. (2024). 'Tehnike umjetne inteligencije u upravljanju autonomnim prometnim sredstvima', Master's thesis, University of Split, Faculty of Maritime Studies, accessed 23 November 2024, https://urn.nsk.hr/urn:nbn:hr:164:001576

Marić N. Tehnike umjetne inteligencije u upravljanju autonomnim prometnim sredstvima [Master's thesis]. Split: University of Split, Faculty of Maritime Studies; 2024 [cited 2024 November 23] Available at: https://urn.nsk.hr/urn:nbn:hr:164:001576

N. Marić, "Tehnike umjetne inteligencije u upravljanju autonomnim prometnim sredstvima", Master's thesis, University of Split, Faculty of Maritime Studies, Split, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:164:001576

Metadata
TitleTehnike umjetne inteligencije u upravljanju autonomnim prometnim sredstvima
Title (english)Artificial intelligence techniques in the management of autonomous vehicles
AuthorNina Marić
MentorIgor Vujović (mentor)
Committee memberEli Marušić (predsjednik povjerenstva)
Committee memberTina Perić (član povjerenstva)
GranterUniversity of Split
Faculty of Maritime Studies
(Department of nautical studies)
Split
Defense date and country2024-09-27, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Traffic and Transport Technology
Abstract
U radu će se pružit uvid u tehnike umjetne inteligencije koje se koriste u upravljanju autonomnim prometnim sredstvima. Autonomna prometna sredstva u pomorstvu predstavljaju samoupravljiva prometna sredstva na moru i kontejnerskim terminalima konstruirana za različite operacije bez izravnog ljudskog upravljanja, koristeći napredne senzore, softver i tehnike umjetne inteligencije. U autonomnom brodarstvu, primjena umjetne inteligencije mijenja pomorsku industriju, donoseći značajne prednosti u smislu sigurnosti, učinkovitosti i ekološke održivosti. Tehnike umjetne inteligencije poput strojnog učenja, dubokog učenja i pojačanog učenja predstavljaju ključni čimbenik u postizanju različitih razina funkcionalnosti autonomnih prometnih sredstava. Koristeći te tehnike autonomni brodovi mogu točnije ploviti, izbjeći sudare, optimizirati rute u stvarnom vremenu i dr. Osim toga, smanjuje se ljudska pogreška, snižavaju operativni troškovi i minimalizira utjecaj pomorskog prijevoza na okoliš. Pojava regulatornih okvira i smjernica u fazama projektiranja i rada na autonomnim prometnim sredstvima omogućit će učinkovitije upravljanje autonomnim pomorskim aktivnostima.
Abstract (english)
This thesis will provide an insight into artificial intelligence techniques in the management of autonomous vehicles. Autonomous maritime vehicles are self-navigating vehicles at sea and in container terminals designed for various operations without direct human control, using advanced sensors, software and artificial intelligence techniques. In autonomous shipping, the application of artificial intelligence is changing the maritime industry, bringing significant benefits in terms of safety, efficiency and environmental sustainability. Artificial intelligence techniques such as machine learning, deep learning and reinforced learning represent a key factor in achieving different levels of functionality for autonomous vehicles. Using these techniques, autonomous ships can navigate more accurately, avoid collisions, optimize routes in real time, etc. In addition, human error is reduced, operating costs are lowered and the impact of maritime transport on the environment is minimized. Emergence of regulatory frameworks and guidelines in the design and work phases of autonomous vehicles will enable more efficient management of autonomous maritime activities.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:164:001576
Study programmeTitle: Maritime Management
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka pomorskog menadžmenta (magistar/magistra inženjer/inženjerka pomorskog menadžmenta)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Created on2024-10-24 08:44:37