dc.contributor.author | Klapálek J. | |
dc.contributor.author | Novák A. | |
dc.contributor.author | Sojka M. | |
dc.contributor.author | Hanzálek Z. | |
dc.date.accessioned | 2023-12-07T15:30:17Z | |
dc.date.available | 2023-12-07T15:30:17Z | |
dc.date.issued | 2021 | |
dc.identifier | V3S-353516 | |
dc.identifier.citation | KLAPÁLEK, J., et al. Car Racing Line Optimization with Genetic Algorithm using Approximate Homeomorphism. In: 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Praha, 2021-09-27/2021-10-01. Piscataway: IEEE, 2021. p. 601-607. ISSN 2153-0866. ISBN 978-1-6654-1714-3. DOI 10.1109/IROS51168.2021.9636503. | |
dc.identifier.isbn | 978-1-6654-1715-0 (print) | |
dc.identifier.isbn | 978-1-6654-1714-3 (online) | |
dc.identifier.issn | 2153-0858 (print) | |
dc.identifier.issn | 2153-0866 (online) | |
dc.identifier.uri | http://hdl.handle.net/10467/112980 | |
dc.description.abstract | In every timed car race, the goal is to drive through the racing track as fast as possible. The total time depends on selection of the racing line. Following a better racing line often decides who wins. In this paper, we solve the optimal racing line problem using a genetic algorithm. We propose a novel racing line encoding based on a homeomorphic
transformation called Matryoshka mapping. We evaluate the fitness of racing lines by lap time estimation using a vehicle model suitable for F1/10 autonomous racing competition. By comparing to the former state-of-the-art, we show that our method is able to find racing lines with lower lap times. Specifically, on one of the testing tracks, we achieve 2.5%
improvement. | eng |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | IEEE | |
dc.relation.ispartof | 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) | |
dc.subject | optimization | eng |
dc.title | Car Racing Line Optimization with Genetic Algorithm using Approximate Homeomorphism | eng |
dc.type | stať ve sborníku | cze |
dc.type | conference paper | eng |
dc.identifier.doi | 10.1109/IROS51168.2021.9636503 | |
dc.relation.projectid | info:eu-repo/grantAgreement/Ministry of Education, Youth and Sports/8A/8A19011/CZ/Arrowhead Tools for Engineering of Digitalisation Solutions/Arrowhead tools MŠMT | |
dc.rights.access | openAccess | |
dc.identifier.wos | 000755125500059 | |
dc.type.status | Peer-reviewed | |
dc.type.version | acceptedVersion | |
dc.identifier.scopus | 2-s2.0-85124368090 | |
dc.relation.conference | 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) | |