Projektiranje sustava autonomne vožnje u Matlab/simulink okruženju

master's thesis

• Title (english): Design of autonomous driving system in Matlab/simulink environment
• Author: Jere Radas
• Mentor: Jadranko Matuško (mentor)
• Committee member: Jadranko Matuško (predsjednik povjerenstva)
• Committee member: Šandor Ileš (član povjerenstva)
• Committee member: Željko Jakopović (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2020-07-10, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Electrical Engineering

Abstract

Autonomna vozila imaju potencijala promijeniti način mobilnosti i transporta u svijetu. Zbog današnje važnosti transporta, ova se tehnologija postavlja na sami vrh pokretača nove industrijske revolucije, što je također čini poželjnom temom za akademski rad. U ovom radu projektiran je sustav praćenja trajektorije za autonomna vozila u Matlab/ Simulink programskom okruženju. Model autonomnog vozila sastoji se od dva dijela: model lateralne i model longitudinalne dinamike. Za svaki dio sintetiziran je odgovarajući sustav upravljanja, odnosno za model lateralne dinamike modelsko prediktivni regulator, a za model longitudinalne dinamike postavljeno je upravljanje u otvorenoj petlji. Modelsko prediktivno upravljanje jaka je optimizacijska strategija upravljanja koja, zbog svojih mogućnosti rješavanja željenog optimizacijskog problema uz postavljena ograničenja nad veličinama sustava, predstavlja jednu od naprednijih modernih metoda upravljanja. Osim vozila, u Matlab okruženju scenarij vožnje sastoji se od ceste po kojoj vozilo vozi i postavljenog senzora kamere koji očitava podatke ceste koji su preoblikovani u reference za odgovarajući regulator. Posljednji dio rada demonstrira funkcionalnost predloženog rješenja i komentira kojim bi se postupcima rad mogao unaprijediti.

Abstract (english)

Autonomous vehicle have the potencial to change the ways of mobility and transportation in the world. Because of today's transportation importance, this technology is placed on the top of initiators of a new industry revolution. This makes this area of technology desirable as a master's thesis. In this thesis, a control system for trajectory tracking that replicates a behavior of an autonomous vehicle is designed in Matlab/Simulink program enviroment . The model of the autonomous vehicle consists of two parts: a model of lateral dynamics and a model of longitudinal dynamics. For the model of lateral dynamics a model predictive controller has been designed and for the model of longitudinal dynamics an open loop system has been set. Model predictive control is a strong optimization control strategy which, because of it's possibilities of solving a desired optimization problem within set limitations, represents one of the most advanced modern control methods. Beside the vehicle, in the Matlab enviroment, the driving scenario consists of a road on which the vehicle is driving and a sensor, placed on the vehicle, that reports data interpreted as a reference for the corresponding controller. Last part of the thesis demonstrates the obtained results and comments with what actions could the autonomous driving system be improved.

• Keywords: dinamika vozila; kinematički model; dinamički model; autonomna vožnja; praćenje trajektorije; YALMIP; modelsko prediktivno upravljanje; scenarij vožnje; Driving Scenario Designer
• Keywords (english): vehicle dynamics; kinematic model; dynamic model; autonomous driving; trajectory tracking; YALMIP; model predictive control; driving scenario; Driving Scenario Designer
• Language: croatian
• URN:NBN: urn:nbn:hr:168:518457
• Study programme: Title: 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 resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-13 13:37:55