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Hyperparameter Optimization Technique in Autonomous Racing Cars exploiting the Leaky Piece and Conquer Fireworks Algorithm

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dc.contributor.authorKim, MyeongJun-
dc.contributor.authorKim, Gun-Woo-
dc.date.accessioned2024-04-17T01:30:13Z-
dc.date.available2024-04-17T01:30:13Z-
dc.date.issued2023-12-
dc.identifier.issn1613-0073-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/70272-
dc.description.abstractThis paper discusses hyperparameter optimization within existing autonomous driving algorithms used in autonomous racing competitions. Existing autonomous driving algorithms vary significantly in performance depending on the setting of hyperparameters, making it important to find the right hyperparameter. To address these issues, we propose the Leaky Piece and Conquer Fireworks method, which improves the efficiency of hyperparameter optimization. Experimental results indicate that, on average, the general Fireworks algorithm is approximately 35.5 times faster than Random Search. Furthermore, the Piece and Conquer Fireworks algorithm and the Leaky Piece and Conquer Fireworks algorithm are about 69.9 and 77.9 times faster, respectively. © 2023 Copyright for this paper by its authors.-
dc.language영어-
dc.language.isoENG-
dc.publisherCEUR-WS-
dc.titleHyperparameter Optimization Technique in Autonomous Racing Cars exploiting the Leaky Piece and Conquer Fireworks Algorithm-
dc.typeArticle-
dc.identifier.scopusid2-s2.0-85189523878-
dc.identifier.bibliographicCitationCEUR Workshop Proceedings, v.3655-
dc.citation.titleCEUR Workshop Proceedings-
dc.citation.volume3655-
dc.type.docTypeConference paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorAutonomous Driving-
dc.subject.keywordAuthorFireworks algorithm-
dc.subject.keywordAuthorHyperparameter Optimization-
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