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

Nicola Barthelmes, Stefan Sicklinger, Markus Zimmermann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

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.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665460262
DOIs
StatePublished - 2022
Event2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022 - Bedford, United Kingdom
Duration: 20 Sep 202222 Sep 2022

Publication series

NameIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
Volume2022-September

Conference

Conference2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022
Country/TerritoryUnited Kingdom
CityBedford
Period20/09/2222/09/22

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