prikaz prve stranice dokumenta Korekcija navika vozača strojnim učenjem
No public access
undergraduate thesis
Korekcija navika vozača strojnim učenjem
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:945348
Kuzman, Jan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Kuzman, J. (2024). Korekcija navika vozača strojnim učenjem (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:945348

Kuzman, Jan. "Korekcija navika vozača strojnim učenjem." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:945348

Kuzman, Jan. "Korekcija navika vozača strojnim učenjem." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:945348

Kuzman, J. (2024). 'Korekcija navika vozača strojnim učenjem', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 28 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:945348

Kuzman J. Korekcija navika vozača strojnim učenjem [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 December 28] Available at: https://urn.nsk.hr/urn:nbn:hr:168:945348

J. Kuzman, "Korekcija navika vozača strojnim učenjem", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:945348

Metadata
TitleKorekcija navika vozača strojnim učenjem
Title (english)Correction of driver habits with machine learning
AuthorJan Kuzman
MentorVinko Lešić (mentor)
Committee memberVinko Lešić (član povjerenstva)
Committee memberFilip Vrbanc (član povjerenstva)
Committee memberMihael Jakšić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-04, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Potrošnja goriva u vozilima je pod velikim utjecajem stila vožnje, koji može varirati od sporog do agresivnog. Koristeći strojno učenje nad prikupljenim podacima iz akcelerometra i žiroskopa, ovaj rad istražuje kako se potrošnja goriva mijenja ovisno o stilu vožnje. Razvijen je model za predikciju potrošnje goriva korištenjem algoritma Random Forest Regression. Podaci su prikupljeni iz senzora ugrađenih u mobilnim uređajima, a obuhvaćaju razdoblje vožnje te su podijeljeni u tri kategorije – agresivna, normalna i spora vožnja. Model je treniran na segmentiranim podacima, a njegova točnost je testiranja na odvojenom i još neviđenom skupu podataka. Postignuta je visoka, skoro savršena, točnost za sve stilove vožnje. Uspješno su implementirani sustavi upozorenja i nagrađivanja vozača koji mogu pomoći u poticanju ekonomičnije vožnje, smanjujući potrošnju goriva i emisije stakleničkih plinova.
Abstract (english)
Fuel consumption in vehicles is greatly influenced by driving style, which can vary from slow to aggressive. Utilizing machine learning on collected data from accelerometers and gyroscopes, this paper investigates how fuel consumption changes depending on the driving style. A model for predicting fuel consumption was developed using the Random Forest Regression algorithm. The data was collected from sensors embedded in mobile devices, covering the driving period and categorized into three categories – aggressive, normal and slow driving. The model was trained on segmented data, and its accuracy was tested on separate and previously unseen dataset. High, nearly perfect accuracy was achieved for all driving styles. Successfully implemented driver warning and reward system can help promote more economical driving, reducing fuel consumption and greenhouse gas emissions.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:945348
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Public note
Created on2024-10-12 21:16:26