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http://dx.doi.org/10.22680/kasa2022.14.2.045

Development of Color Recognition Algorithm for Traffic Lights using Deep Learning Data  

Baek, Seoha (서울대학교 공과대학 기계공학부)
Kim, Jongho (서울대학교 공과대학 기계공학부)
Yi, Kyongsu (서울대학교 공과대학 기계공학부)
Publication Information
Journal of Auto-vehicle Safety Association / v.14, no.2, 2022 , pp. 45-50 More about this Journal
Abstract
The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios.
Keywords
Autonomous Vehicle; Traffic light; V2X data; Camera coordinate; Urban infrastructure data;
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Times Cited By KSCI : 1  (Citation Analysis)
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