Application of digital image on road marking

• Main Authors: Kin-Wai Leong, 梁健偉
• Other Authors: 周家蓓
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/a74683

碩士 === 國立臺灣大學 === 土木工程學研究所 === 107 === In view of the current domestic and international emphasis on road safety and the requirements are constantly improving, road markings as an important part of the road the relevant acceptance and testing standards are currently very lacking. At present, there are two main evaluation indexes commonly used in the international standard for the grading of road marking: one is the luminance coefficient under diffuse illumination (Qd) and the other is coefficient of retroreflected luminance(RL). However, the measurement method of those index and requirements are high, and it is difficult to carry out extensive and constant detection on the general road, and as a result, the reflective capability of different markings on the road is uneven. In view of this, our research proposes to use the on-board camera for image recognition to establish a road marking reflective capability detection system with discriminative effect. Mask R-CNN model is used to find the position of the target road marking in the image, and the brightness of the pixel in the position is taken, after that the average brightness of those pixel is used as the brightness of the road marking. The maximum visible road marking distance is measured by using the different position of the pixel for a same marking in the dual lens to apply the front intersection method. Finally, compare the above data with the coefficient RL, set a photo brightness value that can distinguish the road marking from the minimum road marking''s reflective capability as a threshold for future road marking maintenance reference. The brightness value of the road marking photograph established by the study is consistent with the trend of the grading index RL in different grading, which can reflect the reflective capability and visibility of the road marking. The other part of the research is a subject experiment to explore the data difference between the visual condition and the image recognition of the driver during actual driving, such as: different types of markings, type of pavement where the marking is located, the state of vehicles, impact of external light sources on the subject, etc. According to the experimental results, the visual condition of the subject''s driving the road marking is basically better than the image recognition. The visual distance of different markings corresponds to the RL value, and the visual distance of the flexible pavement is generally It will be higher than the rigid pavement. However, in different age groups, the vehicle''s traveling condition has little effect on the visual distance of the marking. But if there is an external light source, the visible distance of the material selected in this study exceeds the minimum reaction time required under the general road speed limit, and the brightness of the photo of the road marking is also meets with the system''s analysis exceeds the threshold set by the system.