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Automatic Inspection and Evaluation System for Pavement Distress
IEEE transactions on intelligent transportation systems (Print), 2021Pavement distress detection is of significance for road maintenance and traffic safety. Manual pavement distress detection suffers from high workloads, inefficiency, low accuracy, and high cost.
Hongwen Dong +4 more
semanticscholar +1 more source
Horizontal Cracking and Pavement Distress in Portland Cement Concrete Pavement
Designing, Constructing, Maintaining, and Financing Today's Airport Projects, 2002This paper describes how severe spalling and half-depth punchout failures associated with horizontal cracks at the mid-depth of the concrete slabs were observed in continuously reinforced concrete pavement (CRCP) in Texas. A study was conducted to identify the causes of those horizontal cracks and their effect on pavement distress.
Moon C. Won +3 more
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Automated Real-Time Pavement Distress Analysis
Transportation Research Record: Journal of the Transportation Research Board, 1999Pavement distress detection and analysis is an important component of pavement management systems. Conventional visual and manual pavement distress analysis techniques are very costly, time-consuming, dangerous, labor-intensive, tedious, and subjective; have a high degree of variability; are unable to provide meaningful quantitative information; and ...
H. D. Cheng, X. Jiang, J. Li, C. Glazier
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Pavement distress detection and severity analysis
SPIE Proceedings, 2011Automatic recognition of road distresses has been an important research area since it reduces economic loses before cracks and potholes become too severe. Existing systems for automated pavement defect detection commonly require special devices such as lights, lasers, etc, which dramatically increase the cost and limit the system to certain ...
E. Salari, G. Bao
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Pavement distress classification using neural networks
Proceedings of IEEE International Conference on Systems, Man and Cybernetics, 2002A novel approach of applying moment invariants and neural networks to analyze pavement images is presented in this paper. By calculating moment invariants from different types of distress, features are obtained. Then a backpropagation neural network is used to classify these features. This approach is illustrated using randomly selected sample of video
null JaChing Chou +2 more
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Automatic inspection of pavement cracking distress
SPIE Proceedings, 2005This paper presents the image-processing algorithm customized for high-speed, real-time inspection of pavement cracking. In the algorithm, a pavement image is divided into grid cells of 8x8 pixels and each cell is classified as a non-crack or crack cell using the grayscale information of the border pixels.
B. Xu, Y. Huang
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Pavement Distress Under Accelerated Trafficking
Transportation Research Record: Journal of the Transportation Research Board, 1998A test pad was closely monitored for a 6-month period, with 640,000 axle load repetitions applied to the test pavement. The load was applied by the Texas Mobile Load Simulator, a full-scale accelerated loading device. Pavement performance data, such as rutting and cracking, were collected at intervals of 0; 2,500; 5,000; 10,000; 20,000; 40,000; 80,000;
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Automated pavement distress detection using region based convolutional neural networks
International Journal of Pavement Engineering, 2020Automatic pavement crack detection is essential for evaluating maintenance requirements and ensuring driving safety. Crack detection plays a primary role in realising the automatic evaluation of pavement condition.
Eldor B. Ibragimov +3 more
semanticscholar +1 more source
Autonomous pavement distress detection using ground penetrating radar and region-based deep learning
, 2020Many data processing technologies have been utilized for pavement distress detection (e.g., reflection cracks, water-damage pits, and uneven settlements) using ground penetrating radar (GPR).
Jie Gao +4 more
semanticscholar +1 more source
Artificial Life for Pavement Distress Survey
Key Engineering Materials, 2005Automatic recognition of road distresses is of considerable interest since it facilitates road maintenance. We propose the use of artificial life for pavement distress survey. All artificial organisms in the artificial life algorithm exhibit the principle of cooperation which can be found in computer virtues and the hunting process of predators ...
Qi Wang, Hui Zhang
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