Abstract
With the advancement of 3D sensor and information technology, a high-resolution, high-speed 3D line laser imaging system has become available for pavement surface condition data collection. This paper presents preliminary results of a research project sponsored by the U. S. Department of Transportation (DOT) Research and Innovation Technology Administration (RITA) and the Commercial Remote Sensing and Spatial Information (CRS&SI) technology program. The objective of this paper is to validate the capability of 3D laser pavement data gathered during an automated pavement survey. An experimental test, using continuous profile-based laser data collected from Georgia State Route 80 and 275, was conducted to evaluate the performance of 3D line laser imaging technology. Based on the experimental results, the 3D laser pavement data are robust under different lighting conditions and low-intensity contrast conditions and have the capability to deal with different contaminants on a pavement’s surface. It can support an accurate crack width measurement, which will contribute to further crack classification task. The 3D laser pavement data have a good capability to collect cracks that are greater than 2mm wide; however, the data resolution limits the detection of hairline cracks to approximately 1mm. The findings are crucial for transportation agencies to use when determining their automated pavement survey policies. Recommendations for future research are discussed in the paper.
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References
Haas, C., Hendrickson, C.: Computer-based Model of Pavement Surfaces. Transportation Research Record (1260), 91–98 (1990)
Cheng, H.D., Chen, J., Glazier, C., Hu, Y.G.: Novel approach to pavement cracking detection based on fuzzy set theory. Journal of Computing in Civil Engineering 13(4), 270–280 (1999)
Wang, K.C.P.: Designs and implementations of automated systems for pavement surface distress survey. Journal of Infrastructure Systems 6(1), 24–32 (2000)
Lee, B.J., Lee, H.D.: Position-invariant neural network for digital pavement crack analysis. Computer-Aided Civil and Infrastructure Engineering 19(2), 105–118 (2004)
Huang, Y., Tsai, Y.: Enhanced Pavement Distress Segmentation Algorithm Using Dynamic Programming and Connected Component Analysis. Transportation Research Record (2011) (accepted for publication)
Tsai, Y., Li, F.: Critical Assessment of Detecting Asphalt Pavement Cracks under Different Lighting and Low Intensity Contrast Conditions Using Emerging 3D Laser Technology. Journal of Transportation Engineering (2011) (accepted for publication)
Xu, B.: Summary of Implementation of an Artificial Lighting System for Automated Visual Distress Rating System. Presented at Transportation Research Board Annual Meeting (2007)
Hou, Z., Wang, K.C.P., Gong W.: Experimentation of 3d Pavement Imaging through Stereovision. In: Proc. of International Conference on Transportation Engineering, pp. 376–381 (2007)
Kaul, V., Tsai, Y.J., Mersereau, R.M.: Quantitative Performance Evaluation Algorithms for Pavement Distress Segmentation. Transportation Research Record (2153), 106–113 (2010)
Laurent, J., Lefebvre, D.: Development of a New 3d Transverse Laser Profiling System for the Automatic Measurement of Road Cracks. Presented at the 6th Symposium on Pavement Surface Characteristics (2008)
Alekseychuk, O.: Detection of Crack-Like Indications in Digital Radiography by Global Optimisation of a Probabilistic Estimation Function, PhD Thesis, BAM-Dissertationsreihe, Band 18 (2006)
Tsai, Y., Kaul, V., Mersereau, R.M.: Critical Assessment of Pavement Distress Segmentation Methods. Journal of Transportation Engineering 136(1), 11–19 (2010)
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© 2012 RILEM 2012
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Tsai, Y.(., Jiang, C., Wang, Z. (2012). Pavement Crack Detection Using High-Resolution 3D Line Laser Imaging Technology. In: Scarpas, A., Kringos, N., Al-Qadi, I., A., L. (eds) 7th RILEM International Conference on Cracking in Pavements. RILEM Bookseries, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4566-7_17
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DOI: https://doi.org/10.1007/978-94-007-4566-7_17
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-4565-0
Online ISBN: 978-94-007-4566-7
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