Applying Machine Vision Algorithm on Pavement Marking Retroreflectivity Measurement
Journal
Journal of Infrastructure Systems
Journal Volume
29
Journal Issue
4
Start Page
04023027
ISSN
10760342
Date Issued
2023-12-01
Author(s)
Abstract
This preliminary study presents the development of integrating a real-time mobile device with a machine vision algorithm to assess the retroreflectivity of the broken lane lines of in-service road marking. A stereo camera was used as the photometer, and the measuring vehicle's headlights were used as the illumination system. The machine vision algorithm includes marking centroid determination, standard measuring condition control, illumination condition calculation, and luminance measurement. The test results show that the average absolute error percentage of 47 marking samples is 6.1%, with the highest and lowest accuracies of 99.9% and 85.7%, respectively. The left and right lane line (broken line) markings can be evaluated simultaneously in a single pass up to 100 kph. The hardware package, including a stereo camera, a camera support beam, cables, and a laptop computer, costs approximately USD 3,500, which is much lower than the cost of conventional and advanced fully automatic retroreflectometers. Moreover, the developed method is for general usage and can be easily modified and applied to camera sets and vehicle carriers of different specifications. Although the results are promising, the proposed method has some limitations. First, the accuracy decreases when the test section is rough with bumps and dips. Second, this algorithm is not ready for surveying solid lines. Furthermore, the current version can only be implemented under vehicle headlights. Future work can focus on improving the hardware and machine vision algorithm to overcome the challenges.
Subjects
Broken line recognition
Machine vision
Road marking retroreflectivity
Publisher
American Society of Civil Engineers (ASCE)
Type
journal article