Car Racing Line Optimization with Genetic Algorithm using Approximate Homeomorphism

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00353516" target="_blank" >RIV/68407700:21230/21:00353516 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/21:00353516

Výsledek na webu

<a href="http://dx.doi.org/10.1109/IROS51168.2021.9636503" target="_blank" >http://dx.doi.org/10.1109/IROS51168.2021.9636503</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS51168.2021.9636503" target="_blank" >10.1109/IROS51168.2021.9636503</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Car Racing Line Optimization with Genetic Algorithm using Approximate Homeomorphism

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Car Racing Line Optimization with Genetic Algorithm using Approximate Homeomorphism

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/8A19011" target="_blank" >8A19011: Arrowhead Tools for Engineering of Digitalisation Solutions</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

ISBN

978-1-6654-1714-3

ISSN

2153-0858

e-ISSN

2153-0866

Počet stran výsledku

7

Strana od-do

601-607

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Praha

Datum konání akce

27. 9. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000755125500059