Autonomous Car Chasing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00345492" target="_blank" >RIV/68407700:21230/20:00345492 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21240/20:00345492

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-66823-5_20" target="_blank" >https://doi.org/10.1007/978-3-030-66823-5_20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-66823-5_20" target="_blank" >10.1007/978-3-030-66823-5_20</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Autonomous Car Chasing

Popis výsledku v původním jazyce

We developed an autonomous driving system that can chase another vehicle using only images from a single RGB camera. At the core of the system is a novel dual-task convolutional neural network simultaneously performing object detection as well as coarse semantic segmentation. The system was firstly tested in CARLA simulations. We created a new challenging publicly available CARLA Car Chasing Dataset collected by manually driving the chased car. Using the dataset, we showed that the system that uses the semantic segmentation was able to chase the pursued car on average 16% longer than other versions of the system. Finally, we integrated the system into a sub-scale vehicle platform built on a high-speed RC car and demonstrated its capabilities by autonomously chasing another RC car.

Název v anglickém jazyce

Autonomous Car Chasing

Popis výsledku anglicky

We developed an autonomous driving system that can chase another vehicle using only images from a single RGB camera. At the core of the system is a novel dual-task convolutional neural network simultaneously performing object detection as well as coarse semantic segmentation. The system was firstly tested in CARLA simulations. We created a new challenging publicly available CARLA Car Chasing Dataset collected by manually driving the chased car. Using the dataset, we showed that the system that uses the semantic segmentation was able to chase the pursued car on average 16% longer than other versions of the system. Finally, we integrated the system into a sub-scale vehicle platform built on a high-speed RC car and demonstrated its capabilities by autonomously chasing another RC car.

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

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

Computer Vision – ECCV 2020 Workshops, Part IV

ISBN

978-3-030-66822-8

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

16

Strana od-do

337-352

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Glasgow

Datum konání akce

23. 8. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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