prikaz prve stranice dokumenta Estimiranje trajektorije vozila Kalmanovim filtrom za generiranje logičkih scenarija
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master's thesis
Estimiranje trajektorije vozila Kalmanovim filtrom za generiranje logičkih scenarija
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:515897
Pavičić, Pavle
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Pavičić, P. (2021). Estimiranje trajektorije vozila Kalmanovim filtrom za generiranje logičkih scenarija (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:515897

Pavičić, Pavle. "Estimiranje trajektorije vozila Kalmanovim filtrom za generiranje logičkih scenarija." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:515897

Pavičić, Pavle. "Estimiranje trajektorije vozila Kalmanovim filtrom za generiranje logičkih scenarija." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:515897

Pavičić, P. (2021). 'Estimiranje trajektorije vozila Kalmanovim filtrom za generiranje logičkih scenarija', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 09 August 2024, https://urn.nsk.hr/urn:nbn:hr:168:515897

Pavičić P. Estimiranje trajektorije vozila Kalmanovim filtrom za generiranje logičkih scenarija [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 August 09] Available at: https://urn.nsk.hr/urn:nbn:hr:168:515897

P. Pavičić, "Estimiranje trajektorije vozila Kalmanovim filtrom za generiranje logičkih scenarija", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:515897

Metadata
TitleEstimiranje trajektorije vozila Kalmanovim filtrom za generiranje logičkih scenarija
Title (english)Vehicle Trajectory Estimation with the Kalman filter for Generating Logical Scenarios
AuthorPavle Pavičić
MentorIvan Marković (mentor)
Committee memberIvan Marković (predsjednik povjerenstva)
Committee memberMarija Seder (član povjerenstva)
Committee memberIvan Petrović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract
Cilj ove teze je istražiti estimaciju stanja vozila korištenjem Kalmanovog filtra s različitim modelima vozila. Estimirani parametri koji se obrađuju u ovom istraživanju su: putanja vozila, masa i međuosovinski razmak. Budući da se autonomna vozila brzo razvijaju, ove vrste procjena mogu naći primjenu u brojnim sustavima poput sustava automatskog kočenja (skraćeno: ABS) koji koristi precizne vrijednosti mase i duljine vozila. Također, procjena stanja vozila u velikoj mjeri može pomoći u stvaranju simulacije logičkih scenarija prometa koji se koriste za daljnji razvoj autonomnih sustava vozila. Skupovi podataka korišteni tijekom istraživanja generirani su putem programa ASM ModelDesk, dok su obrada signala, razvoj modela i proračun parametara postignuti kroz program MATLAB i programski jezik Python.
Abstract (english)
This thesis aims to explore estimation of vehicle’s states by using Kalman filter with different vehicle models. The parameters estimated for this research are vehicle trajectory, mass and wheel base. Since autonomous vehicles are rapidly developing, these types of estimations can find use in numerous vehicle systems such as automatic braking system (abbreviated as: ABS) which needs accurate vehicle mass and vehicle length value. Also, estimation of vehicle’s states can largely help in generation of simulated logical traffic scenarios used for further development of autonomous vehicle systems. Datasets used for this research are generated via program ASM ModelDesk, while signal processing, model development and parameter calculation were achieved through MATLAB program and Python programming language.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:515897
Study programmeTitle: Electrical Engineering and Information Technology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije (magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije)
Type of resourceText
File originBorn digital
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Created on2023-01-13 15:48:26