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nighttime Traffic Light Location Based on Binocular Vision and Electronic Map

Nighttime Traffic Light Location Based on Binocular Vision a...

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第三十九届中国控制会议

作者： Lan Junfeng Fang Tiyu Li Jinping School of Information Science and Engineering University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Shandong College and University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-year

Autonomous driving needs to obtain various traffic information promptly to make decisions, and the accurate positioning of traffic light in real time is one of the key points to realize autonomous driving. Up to now, there are many interesting and practical researches related to the positioning. However, most of the scholars are doing researches of daylight traffic light location. At night, Neon lights, street lights, car lights and other factors may have a serious impact on the accurate positioning of traffic lights. How to remove the influence of these factors is a big challenge in autonomous driving. We propose a practical approach to address this challenge. The motivation of this approach is as follows: Firstly, GPS information and electronic map are used to estimate the distance and direction of the current position relative to the traffic light;secondly, binocular vision is applied to get the depth, orientation and other information of each area in the image, excluding the interference area outside the scope of the traffic light;thirdly, use some methods to positioning the traffic light, including brightness value division, geometric features analysis, circular degree detection, and then the status of the traffic light can be recognized through the HSV color space. The experimental result shows that the positioning accuracy of this method is more than 95%, the average of processing time for each image is 301 ms, which can meet the requirements of accuracy and real-time.

关键词： Traffic light nighttime detection Binocular vision Electronic map GPS position

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