The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
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La technologie de conduite autonome suscite actuellement beaucoup d’attention en tant que technologie qui jouera un rôle dans la prochaine génération de mobilité. Pour une conduite autonome en zone urbaine, il est nécessaire de reconnaître diverses informations. La reconnaissance des feux de circulation est particulièrement importante lors des carrefours. Dans cet article, la technologie de reconnaissance des feux de circulation développée par les auteurs a été évaluée à l’aide des données de capteurs embarqués lors de la conduite autonome dans la zone riveraine de Tokyo, comme exemple de technologie de reconnaissance des feux de circulation. Sur la base des résultats, il a été constaté que les feux de circulation pouvaient être reconnus avec une précision d'environ 99 % pour prendre la décision d'approcher une intersection. Cependant, les résultats de l'évaluation ont également confirmé que la reconnaissance des feux de circulation devenait difficile dans des situations impliquant l'occlusion par un autre objet, l'assimilation de l'arrière-plan, des conditions nocturnes et un contre-jour par la lumière du soleil. Il a également été confirmé que ces effets sont pour la plupart temporaires et n'affectent pas de manière significative la prise de décision d'entrer dans les intersections en raison de l'utilisation des informations provenant de plusieurs feux de circulation installés à une intersection. D'un autre côté, on s'attend à ce que la reconnaissance avec les caméras embarquées actuelles devienne techniquement difficile dans les situations dans lesquelles tous les feux de circulation ne sont pas visuellement reconnaissables en raison des effets de l'éclairage arrière ou avant par la lumière du soleil lorsqu'ils sont arrêtés sur la ligne d'arrêt d'une intersection. Cet article résume ces résultats et présente la nécessité d'une installation appropriée de feux de signalisation dans l'hypothèse d'une reconnaissance par des caméras embarquées.
Naoki SUGANUMA
Kanazawa University
Keisuke YONEDA
Kanazawa University
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Naoki SUGANUMA, Keisuke YONEDA, "Current Status and Issues of Traffic Light Recognition Technology in Autonomous Driving System" in IEICE TRANSACTIONS on Fundamentals,
vol. E105-A, no. 5, pp. 763-769, May 2022, doi: 10.1587/transfun.2021WBI0002.
Abstract: Autonomous driving technology is currently attracting a lot of attention as a technology that will play a role in the next generation of mobility. For autonomous driving in urban areas, it is necessary to recognize various information. Especially, the recognition of traffic lights is important in crossing intersections. In this paper, traffic light recognition technology developed by the authors was evaluated using onboard sensor data during autonomous driving in the Tokyo waterfront area as an example of traffic light recognition technology. Based on the results, it was found that traffic lights could be recognized with an accuracy of approximately 99% to carry out the decision making for intersection approaching. However, from the evaluation results, it was also confirmed that traffic light recognition became difficult under situations involving occlusion by other object, background assimilation, nighttime conditions, and backlight by sunlight. It was also confirmed that these effects are mostly temporary, and do not significantly affect decision-making to enter intersections as a result of utilizing information from multiple traffic lights installed at an intersection. On the other hand, it is expected that recognition with current onboard cameras will become technically difficult during situations in which not all traffic lights are visually recognizable due to the effects of back or front light by sunlight when stopped at the stop line of an intersection. This paper summarizes these results and presents the necessity of appropriate traffic light installation on the assumption of recognition by onboard cameras.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2021WBI0002/_p
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@ARTICLE{e105-a_5_763,
author={Naoki SUGANUMA, Keisuke YONEDA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Current Status and Issues of Traffic Light Recognition Technology in Autonomous Driving System},
year={2022},
volume={E105-A},
number={5},
pages={763-769},
abstract={Autonomous driving technology is currently attracting a lot of attention as a technology that will play a role in the next generation of mobility. For autonomous driving in urban areas, it is necessary to recognize various information. Especially, the recognition of traffic lights is important in crossing intersections. In this paper, traffic light recognition technology developed by the authors was evaluated using onboard sensor data during autonomous driving in the Tokyo waterfront area as an example of traffic light recognition technology. Based on the results, it was found that traffic lights could be recognized with an accuracy of approximately 99% to carry out the decision making for intersection approaching. However, from the evaluation results, it was also confirmed that traffic light recognition became difficult under situations involving occlusion by other object, background assimilation, nighttime conditions, and backlight by sunlight. It was also confirmed that these effects are mostly temporary, and do not significantly affect decision-making to enter intersections as a result of utilizing information from multiple traffic lights installed at an intersection. On the other hand, it is expected that recognition with current onboard cameras will become technically difficult during situations in which not all traffic lights are visually recognizable due to the effects of back or front light by sunlight when stopped at the stop line of an intersection. This paper summarizes these results and presents the necessity of appropriate traffic light installation on the assumption of recognition by onboard cameras.},
keywords={},
doi={10.1587/transfun.2021WBI0002},
ISSN={1745-1337},
month={May},}
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TY - JOUR
TI - Current Status and Issues of Traffic Light Recognition Technology in Autonomous Driving System
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 763
EP - 769
AU - Naoki SUGANUMA
AU - Keisuke YONEDA
PY - 2022
DO - 10.1587/transfun.2021WBI0002
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E105-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 2022
AB - Autonomous driving technology is currently attracting a lot of attention as a technology that will play a role in the next generation of mobility. For autonomous driving in urban areas, it is necessary to recognize various information. Especially, the recognition of traffic lights is important in crossing intersections. In this paper, traffic light recognition technology developed by the authors was evaluated using onboard sensor data during autonomous driving in the Tokyo waterfront area as an example of traffic light recognition technology. Based on the results, it was found that traffic lights could be recognized with an accuracy of approximately 99% to carry out the decision making for intersection approaching. However, from the evaluation results, it was also confirmed that traffic light recognition became difficult under situations involving occlusion by other object, background assimilation, nighttime conditions, and backlight by sunlight. It was also confirmed that these effects are mostly temporary, and do not significantly affect decision-making to enter intersections as a result of utilizing information from multiple traffic lights installed at an intersection. On the other hand, it is expected that recognition with current onboard cameras will become technically difficult during situations in which not all traffic lights are visually recognizable due to the effects of back or front light by sunlight when stopped at the stop line of an intersection. This paper summarizes these results and presents the necessity of appropriate traffic light installation on the assumption of recognition by onboard cameras.
ER -