Digital Map Based Signal State Recognition of Far Traffic Lights with Low Brightness

Accurate state recognition of traffic lights is important for a safe urban drive of autonomous vehicles. A traffic light with lower luminance than its ambient is difficult to recognize particularly in a distant. This paper proposes a strategy that improves accuracy of signal state recognition of distant traffic lights with low luminance. Digital map is used to get candidate regions of traffic lights on a captured image. Each candidate is cropped and resized to equalize the size of lamp area on the image. On the resized images, brightness channel image is modified by enhancing pixels that have hue value in the range of traffic signal color. Then, high value pixels on the SV m image, which is the multiplied image of the salutation channel and the modified brightness channel, is regarded as candidates of lamp area. This strategy attempts to emphasize traffic signal lights darker than its ambient. Experiments in real driving data showed the performance of the proposed method.