Simulations for Training Machine Learning Models for Autonomous Vehicles

dc.contributor.advisorTunnel, Raimond-Hendrik, juhendaja
dc.contributor.advisorMatiisen, Tambet, juhendaja
dc.contributor.authorToompea, Kertu
dc.contributor.otherTartu Ülikool. Loodus- ja täppisteaduste valdkondet
dc.contributor.otherTartu Ülikool. Arvutiteaduse instituutet
dc.date.accessioned2023-10-05T11:10:28Z
dc.date.available2023-10-05T11:10:28Z
dc.date.issued2020
dc.description.abstractTraining machine learning models for autonomous vehicles requires a lot of data which is time consuming and tedious to label manually. Simulated virtual environments help to automate this process. In this work these virtual environments are called simulations. The goal of this thesis is to survey the most suitable simulations for off-road vehicles (while not discarding the urban option). Only the simulations which provide labeled output data, are included in this work. The chosen 12 simulations are surveyed based on the information found online. The simulations are then analyzed based on the predefined features and categorized according to their suitability for training machine learning models for off-road vehicles. The results are shown in a table for comparison. The main purpose of this work is to map the seemingly large landscape of simulations and give a compact picture of the situation.et
dc.identifier.urihttps://hdl.handle.net/10062/93340
dc.language.isoenget
dc.publisherTartu Ülikoolet
dc.rightsopenAccesset
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSimulationset
dc.subjectenvironmentset
dc.subjectoff-roadet
dc.subjectautonomous vehicleset
dc.subjectsensorset
dc.subjectmachine learninget
dc.subjectautomated labelinget
dc.subjectsurveyet
dc.subjectoverviewet
dc.subject.otherbakalaureusetöödet
dc.subject.otherinformaatikaet
dc.subject.otherinfotehnoloogiaet
dc.subject.otherinformaticset
dc.subject.otherinfotechnologyet
dc.titleSimulations for Training Machine Learning Models for Autonomous Vehicleset
dc.typeThesiset

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