The impact of the camera setup on the visibility rate of traffic lights

Nicola Barthelmes, Stefan Sicklinger, Markus Zimmermann

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

5 Zitate (Scopus)

Abstract

Continuous and reliable object detection is essential for advanced driving assistant systems and in particular for fully automated vehicles. Most research focuses on developing object detection algorithms and optimizing the rate of successful object identifications on image frames. However, the sensor position as a relevant design variable is not considered, although it significantly influences whether an object is detectable by the camera, or if it is outside of the field of view or occluded by another traffic participant. This paper introduces a method to assess different camera setups to optimize traffic light visibility. We show that appropriate positioning of the cameras can improve the visibility of a traffic light by up to 90% as a vehicle approaches a junction. Furthermore, we show that the combination of a near-field camera with a long-range camera achieves a more robust result than using a single multi-purpose camera.

OriginalspracheEnglisch
Titel2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9781665460262
DOIs
PublikationsstatusVeröffentlicht - 2022
Veranstaltung2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022 - Bedford, Großbritannien/Vereinigtes Königreich
Dauer: 20 Sept. 202222 Sept. 2022

Publikationsreihe

NameIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
Band2022-September

Konferenz

Konferenz2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022
Land/GebietGroßbritannien/Vereinigtes Königreich
OrtBedford
Zeitraum20/09/2222/09/22

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