TY - GEN
T1 - The impact of the camera setup on the visibility rate of traffic lights
AU - Barthelmes, Nicola
AU - Sicklinger, Stefan
AU - Zimmermann, Markus
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85140957612&partnerID=8YFLogxK
U2 - 10.1109/MFI55806.2022.9913851
DO - 10.1109/MFI55806.2022.9913851
M3 - Conference contribution
AN - SCOPUS:85140957612
T3 - IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
BT - 2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022
Y2 - 20 September 2022 through 22 September 2022
ER -