Application of Laser-based Measurement Systems in Pavement Management
Document Type : Original Article
Authors
1 Assistant Professor, Civil Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran.
2 M.Sc., Grad., Civil Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran.
10.22034/road.2021.103507
Abstract
The road pavement surface has an important role in relation to address the primary demands of vehicle movement, such as safety and eco-compatibility. In order to reduce road maintenance and rehabilitation costs and optimize the service condition of road networks, pavement management systems (PMS) need detailed and reliable data of the highway network characteristics. Laser imaging devices can be employed to collect information on an in-service pavement surface layer through a single measurement with data homogeneity and representativeness in an innovative method. With the recent developments in 3D laser sensors and information technology, high-speed 3D line laser imaging systems with high-resolution has been introduced for measuring key features of pavement surface condition. This research presents some of the key developments in recent years for laser-based distress measurement systems and explains the technology used in laser-based crack measurement system. Laser-based systems key features are introduced and compared with former data collection methods. These new systems are evaluated and described in terms of their applicability and potential for future developments.
Keywords
-Akgul, M., H. Yurtseven, S. Akburak, M. Demir, H. K. Cigizoglu, T. Ozturk, M. Eksi and A. O. Akay (2017). "Short term monitoring of forest road pavement degradation using terrestrial laser scanning." Measurement 103, pp.283-293.
-Bitelli, G., A. Simone, F. Girardi and C. Lantieri (2012), "Laser scanning on road pavements: a new approach for characterizing surface texture." Sensors NO.12(7), pp.9110-9128.
-Chang, K.-T., J. Chang and J.-K. Liu (2005), "Detection of Pavement Distresses Using 3D Laser Scanning Technology".
-Chen, D., C. Ling, T. Wang, Q. Su and A. Ye., (2018), "Prediction of tire-pavement noise of porous asphalt mixture based on mixture surface texture level and distributions." Construction and Building Materials, No.173, pp.801-810.
-Chen, J., X. Huang, B. Zheng, R. Zhao, X. Liu, Q. Cao and S. Zhu., (2019), "Real-time identification system of asphalt pavement texture based on the close-range photogrammetry,
"Construction and Building Materials, 226, pp.910-919.
"Construction and Building Materials, 226, pp.910-919.
-Di Mascio, P. and L. Moretti, (2019), "Implementation of a pavement management system for maintenance and rehabilitation of airport surfaces." Case Studies in Construction Materials, e.20015.
-Fukuhara, T., K. Terada, M. Nagao, A. Kasahara and S. Ichihashi, (1990), "Automatic pavement-distress-survey system." Journal of Transportation Engineering, pp.280-286.
-Gong, H., Y. Sun, Z. Mei and B. Huang, (2018), "Improving accuracy of rutting prediction for mechanistic-empirical pavement design guide with deep neural networks." Construction and Building Materials, 190, pp.710-718.
-Hoang, N.-D., (2019), "Automatic detection of asphalt pavement raveling using image texture based feature extraction and stochastic gradient descent logistic regression." Automation in Construction,
105,102843.
105,102843.
-Inzerillo, L., G. Di Mino and R. Roberts, (2018), "Image-based 3D reconstruction using traditional and UAV datasets for analysis of road pavement distress." Automation in Construction, pp.457-469.
-Jiang, C. and Y. Tsai (2015), "Enhanced Crack Segmentation Algorithm Using 3D Pavement Data." Journal of Computing in Civil Engineering 30, 04015050.
-Kertész, I., T. Lovas and A. Barsi (2008), "Photogrammetric pavement detection system", ISPRS, Citeseer.
-Laurent, J., J. F. Hébert, D. Lefebvre and Y. Savard (2012), "High-speed network level road texture evaluation using 1mm resolution transverse 3D profiling sensors using a digital sand patch model. International Conference on Maintenance and Rehabilitation of Pavements and Technological Control, 7th, (2012), Auckland, New Zealand.
-Laurent, J., D. Lefebvre and E. Samson (2008), "Development of a New 3D Transverse Laser Profiling System for the Automatic Measurement of Road Cracks."
-Li, W., J. Huyan, S. Tighe, Q.-q. Ren and Z.-y. Sun (2017), "Three-Dimensional Pavement Crack Detection Algorithm Based on Two-Dimensional Empirical Mode Decomposition." Journal of Transportation Engineering, Part B: Pavements 143004017005.
-Lin, J.-D. and M.-C. Ho, (2016), "A comprehensive analysis on the pavement condition indices of freeways and the establishment of a pavement management system." Journal of Traffic and Transportation Engineering (English Edition) 3(5), pp.456-466.
-Meegoda, J. N., S. Gao, S. Liu and N. C. Gephart (2013), "Pavement texture from high-speed laser for pavement management system." International Journal of Pavement Engineering, 14(7), pp.697-705.
-Slob, S. and H. Hack (2004), 3D Terrestrial Laser Scanning as a New Field Measurement and Monitoring Technique, 104, 179-189.
-Tsai, Y.-C. J. and F. Li, (2012), "Critical assessment of detecting asphalt pavement cracks under different lighting and low intensity contrast conditions using emerging 3D laser technology." Journal of Transportation Engineering 138, pp.649-656.
-Tsai, Y. J., C. Jiang and Z. Wang, (2012),
"Pavement Crack Detection Using High-Resolution 3D Line Laser Imaging Technology, 7th RILEM International Conference on Cracking in Pavements, Springer.
"Pavement Crack Detection Using High-Resolution 3D Line Laser Imaging Technology, 7th RILEM International Conference on Cracking in Pavements, Springer.
-Wang, W., X. Yan, H. Huang, X. Chu and M. Abdel-Aty, (2011), "Design and verification of a laser based device for pavement macrotexture measurement." Transportation Research Part C: Emerging Technologies, 19, pp.682-694.
-Yousaf, M. H., K. Azhar, F. Murtaza and F. Hussain (2018), "Visual analysis of asphalt pavement for detection and localization of potholes", Advanced Engineering Informatics 38, pp.527-537.
-Zhang, A., K. C. P. Wang, B. Li, E. Yang, X. Dai, Y. Peng, Y. Fei, Y. Liu, J. Q. Li and C. Chen, (2017), "Automated Pixel-Level Pavement Crack Detection on 3D Asphalt Surfaces Using a Deep-Learning Network", Computer-Aided Civil and Infrastructure Engineering, 10(32), pp.805-819.
-Zhang, D., Q. Li, Y. Chen, M. Cao, L. He and B. Zhang (2017), "An efficient and reliable coarse-to-fine approach for asphalt pavement crack detection." Image and Vision Computing, 57, pp.130-147.
-Zhang, D., Q. Zou, H. Lin, X. Xu, L. He, R. Gui and Q. Li, (2018), "Automatic pavement defect detection using 3D laser profiling technology." Automation in Construction, 96, pp.350-365.