Quality control of micro-milling treatment on tunnel concrete pavement using 3D range data

References

• Bitelli, G., et al., 2012. Laser scanning on road Pavements: A New Approach for Characterizing surface texture. Sensors, 12 (7), 9110–9128.
   PubMed Web of Science ®Google Scholar
• Cackler, E. T., Harrington, D. S., and Ferragut, T., 2006. Evaluation of US and European concrete pavement noise reduction methods.
   Google Scholar
• Chen, D., 2020. Evaluating asphalt pavement surface texture using 3D digital imaging. International Journal of Pavement Engineering, 21 (4), 416–427.
   Web of Science ®Google Scholar
• EI Gendy, A., et al., 2011. Stereo-vision applications to reconstruct the 3D texture of pavement surface. International Journal of Pavement Engineering, 12 (3), 263–273.
   Web of Science ®Google Scholar
• Hao, X., et al., 2015. 3D detection of the groove wear degree on cement concrete pavement. Chinese Journal of Scientific Instrument, 36 (08), 1767–1773.
   Google Scholar
• Hu, X., and Walubita, L.F., 2011. Effects of layer interfacial bonding conditions on the mechanistic responses in asphalt pavements. Journal of Transportation Engineering, 137 (1), 28–36.
   Google Scholar
• Huang, X.M., Xu, T., and Zeng, L, 2008. Choice of pavement structure in road tunnel based on grey target theory. Journal of Highway and Transportation Research and Development, 25 (8), 1–5.
   Google Scholar
• Hung, S.S., Rezaei, A., and Harvey, J.T, 2014. Effects of milling and other repairs on smoothness of overlays on asphalt pavements. Transportation Research Record Journal of the Transportation Research Board, 2408 (1), 86–94.
   Google Scholar
• Lai, J.S., et al., 2009. Georgia's Pavement Preservation with Micromilling and Thin Asphalt Overlay (No. 09-1857).
   Google Scholar
• Laurent, J., Lefebvre, D., and Samson, E., 2008. Development of a new 3D transverse laser profiling system for the automatic measurement of road cracks. In Symposium on Pavement Surface Characteristics, 6th, 2008, Portoroz, Slovenia.
   Google Scholar
• Lee, M.H., Chou, C.P., and Li, K.H, 2009. Automatic measurement of runway grooving construction for pavement skid evaluation. Automation in Construction, 18 (6), 856–863.
   Web of Science ®Google Scholar
• Li, L.I., et al., 2013. Line-structured light image processing procedure for pavement rut detection. Journal of Tongji University, 41 (5), 710–771.
   Google Scholar
• Li, L., et al., 2017. Automated runway groove measurement and evaluation. Ksce Journal of Civil Engineering, 21 (3), 758–765.
   Web of Science ®Google Scholar
• Li, B., et al., 2020. Automatic classification of pavement crack using deep convolutional neural network. International Journal of Pavement Engineering, 21 (4), 457–463.
   Web of Science ®Google Scholar
• Liu, Y., Tian, B., and Niu, K.M, 2012. Skid-resistance and denoising properties of cement concrete pavement with different surface texture. Journal of Highway and Transportation Research and Development, 29 (1), 28–33.
   Google Scholar
• Luo, W., et al., 2014. Surface drainage evaluation for rigid pavements using an inertial measurement unit and 1-mm three-dimensional texture data. Transportation Research Record Journal of the Transportation Research Board, 2457 (1), 121–128.
   Google Scholar
• McGhee, K.H, 2004. Automated pavement distress collection techniques (Vol. 334). Transportation Research Board.
   Google Scholar
• MOT, C.H.N., 2004. Code for design of road tunel. JTG D70-2004, Ministry of Transport of the People’s Republic of China.
   Google Scholar
• Qiu, S., et al., 2018. A comprehensive system for AASHTO PP69-10-based pavement rut evaluation using 1-mm 3D pavement surface model. International Journal of Pavement Engineering, 19 (6), 489–501.
   Web of Science ®Google Scholar
• QTSB, LNP., 2012. Technology specifications for design and construction of ultra-thin friction course. DB 21/T 1995-2012, Liao Ning province Quality and Technical Supervision Bureau, the People’s Republic of China.
   Google Scholar
• Tashman, L., et al., 2008. Evaluation of construction practices that influence the bond strength at the interface between pavement layers. Journal of Performance of Constructed Facilities, 22 (3), 154–161.
   Web of Science ®Google Scholar
• Tsai, Y.C. and Chatterjee, A., 2017. Pothole detection and Classification using 3D technology and Watershed method. Journal of Computing in Civil Engineering, 32 (2), 04017078:1-7.
   Web of Science ®Google Scholar
• Tsai, Y., Wu, Y., and Lai, J, 2012. Ridge-to-valley depth measured with road profiler to control micro-milled pavement textures for super-thin resurfacing on i-95. Transportation Research Record Journal of the Transportation Research Board, 2306 (1), 144–150.
   Google Scholar
• Tsai, Y., Wu, Y., and Lewis, Z., 2013. Full-lane coverage micro-milling pavement-surface quality control using emerging 3d line laser imaging technology. Journal of Transportation Engineering, 140 (2), 04013006:1-8.
   Google Scholar
• Wang, S.Y, 2010. Influence factors of bond performance between asphalt surface layer and semi-rigid base. Journal of Traffic & Transportation Engineering, 2 (04), 13–15.
   Google Scholar
• Wang, K.C., et al., 2012. Potential measurement of pavement surface texture based on three-dimensional image data (No. 12-4046).
   Google Scholar
• Xin, Q., et al., 2017. Three-dimensional characterisation of asphalt pavement macrotexture using laser scanner and micro element. Road Materials and Pavement Design, 18 (Sup 3), 190–199.
   Google Scholar
• Yan, K.Z., et al., 2009. Effect of bond condition on overlay performance. Journal of Hunan University, 36 (5), 11–15.
   Google Scholar
• Yang, X.L., et al., 2003. Field survey and analysis about skid resistance of tunnel pavements. Highway, 12, 136–140.
   Google Scholar
• Zhang, X.H., et al., 2016. Discussion on application of milling technology to improve skid performance of cement concrete pavement in tunnel. Journal of China & Foreign Highway, 2, 62–65.
   Google Scholar
• Zhou, X.L., et al., 2014. Measurement method for mean texture depth of asphalt pavement based on laser vision. China Journal of Highway & Transport, 27 (3), 11–16.
   Google Scholar