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  • 1
    Online Resource
    Online Resource
    Erratum for “Machine Learning for Crack Detection: Review and Model Performance Comparison” by Yung-An Hsieh and Yichang James Tsai
    American Society of Civil Engineers (ASCE) ; 2021
    In:  Journal of Computing in Civil Engineering Vol. 35, No. 1 ( 2021-01)
    Details
    In: Journal of Computing in Civil Engineering, American Society of Civil Engineers (ASCE), Vol. 35, No. 1 ( 2021-01)
    Type of Medium: Online Resource
    ISSN: 0887-3801 , 1943-5487
    URL: Article
    DOI: 10.1061/(ASCE)CP.1943-5487.0000939
    Language: English
    Publisher: American Society of Civil Engineers (ASCE)
    Publication Date: 2021
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  • 2
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    Multiyear Pavement-Rehabilitation Planning Enabled by Geographic Information System: Network Analyses Linked to Projects
    SAGE Publications ; 2004
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 1889, No. 1 ( 2004-01), p. 21-30
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 1889, No. 1 ( 2004-01), p. 21-30
    Abstract: A pavement-rehabilitation planning system enabled by a geographical information system (GIS) is described; it can perform multiyear projectlinked network pavement-rehabilitation analyses subject to funding availability, minimum performance requirements, and other constraints. The system first uses information on the current and historical project-level pavement-condition evaluation stored in the central database to forecast project performance ratings and distresses. It then determines appropriate rehabilitation methods and costs and, finally, calculates life-cycle costeffectiveness ratios for all projects in the pavement network. With this information, the program performs analyses to determine multiyear minimum funding required to meet prescribed pavement-performance requirements and constraints and to determine optimum pavementrehabilitation plans subject to funding availability and other requirements, such as balancing funding distribution or future pavement performance among state congressional districts or Georgia Department of Transportation (GDOT) districts. The system uses dynamic segmentation to create GIS maps, links them with the central database and network analysis results, and thus allows users to make changes to the rehabilitation plans directly on the GIS maps and have the changes reflected automatically in the database. Several examples using the actual data on historical pavement condition evaluations from GDOT are presented to illustrate the capabilities of the system.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/1889-03
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2004
    detail.hit.zdb_id: 2403378-9
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  • 3
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    Online Resource
    Framework and Strategy for Implementing an Information Technology-Based Pavement Management System
    SAGE Publications ; 2002
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 1816, No. 1 ( 2002-01), p. 56-64
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 1816, No. 1 ( 2002-01), p. 56-64
    Abstract: The advent of information and telecommunication technologies has had significant effects on the development and implementation of pavement management systems (PMSs) for state departments of transportation (DOTs) and also fosters great opportunities for improving states' highway pavement conditions through increased productivity and effectiveness in managing their highway pavement information. However, it still remains a challenge for state DOTs to successfully implement an integrated PMS due to the complexity of PMS and many issues involved in the development and implementation that need to be resolved. The development and implementation of an information technology (IT)-based PMS by the Georgia Department of Transportation is presented. On the basis of existing pavement management practices by Georgia DOT, the needs and concerns for improvements are identified in light of the advent of IT. The development of the conceptual IT-based PMS framework to meet Georgia DOT’s needs is first presented. The strategies for developing and implementing an integrated PMS are then presented, and the benefits of adopting the strategies are discussed. The need for incorporating a common spatial and temporal reference system to ensure system compatibility and integration for all the databases is discussed. Seven modules of this integrated IT-based PMS have been implemented, including the computerized pavement condition evaluation system, historical pavement performance data conversion and filtering system, network-level data management and analysis system, geographic information system analysis and visualization system, rehabilitation treatment decision system, highway maintenance management system, and the knowledge-based system for diagnosing pavement distress causes. Four modules currently under development are also described.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/1816-07
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2002
    detail.hit.zdb_id: 2403378-9
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  • 4
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    Online Resource
    Ridge-to-Valley Depth Measured with Road Profiler to Control Micromilled Pavement Textures for Super-Thin Resurfacing on I-95
    SAGE Publications ; 2012
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2306, No. 1 ( 2012-01), p. 144-150
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2306, No. 1 ( 2012-01), p. 144-150
    Abstract: Funding shortages create pavement preservation challenges for state departments of transportation (DOTs). The Georgia DOT developed an innovative micromilling resurfacing method as a cost-effective way to preserve its pavements. The new method can save more than $5 million on an I-95 project of 84 lane miles. To ensure that the micromilled surface texture has a good bond and good runoff capability, the Georgia DOT established a stringent ridge-to-valley-depth (RVD) specification. Preliminary tests were conducted on an I-75 project with a circular track meter and an ultralight inertia profiler, but the RVD was first measured with a laser road profiler for the entire 84 lane miles of the I-95 project. The rough and smooth micromilled pavement surfaces have been studied and compared through an exploration of their statistical characteristics and patterns. Results from four 0.5-mi segments showed that both smooth and rough surface textures revealed normal distributions, although a smooth surface had a slight lognormal distribution. The smooth surface had a mean of about 2.5 mm and a standard deviation of 0.9 mm. The rough surface had a mean of about 4.6 mm and a standard deviation of about 1.1 mm. The cumulative percentage curves for both rough and smooth surface textures showed that the mean RVD value of 3.2 mm could effectively differentiate rough and smooth surfaces. The effects of different base lengths on the RVD were studied, and results showed that a 100-mm base length was adequate to differentiate between smooth and rough surfaces.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2306-17
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2012
    detail.hit.zdb_id: 2403378-9
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  • 5
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    Online Resource
    Automated Superelevation Measurement Method Using a Low-Cost Mobile Device: An Efficient, Cost-Effective Approach Toward Intelligent Horizontal Curve Safety Assessment
    SAGE Publications ; 2017
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2621, No. 1 ( 2017-01), p. 62-70
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2621, No. 1 ( 2017-01), p. 62-70
    Abstract: The horizontal curve is one of the focal points of roadway safety because this curve plays a critical role in transitioning vehicles between tangent roadway sections; moreover, car crashes are frequently concentrated on horizontal curves despite their disproportionate length in the road network. As a critical safety property of horizontal curves, superelevation is crucial to vehicle safety because it counteracts the lateral acceleration produced in vehicles when they travel the curves. Despite the emergence of several sensing-based methods in recent years, labor-intensive and time-consuming manual superelevation evaluation is often carried out by transportation agencies because the newer methods usually demand expensive equipment and complicated operations. Transportation agencies are in urgent need of low-cost, reliable alternatives to improve their data collection practices. This paper proposes an automated superelevation measurement method using inexpensive mobile devices. The proposed method integrates and processes sensing data from a mobile device and derives superelevation by using fundamental vehicle kinematics at a horizontal curve. Kalman filtering–based noise reduction, regression-based radius computation, and complementary-filtering-based rolling angle computation methods are introduced to achieve accurate results despite low-frequency, noisy signals from the inexpensive devices. An experimental test on SR-2 in Georgia demonstrates that the proposed method delivers results with accuracies comparable to those of a lidar-based method. A case study of high friction surface treatment site selection using a ball bank indicator shows that the proposed method is a promising alternative for transportation agencies to achieve low-cost yet reliable data collection for safety analysis and improvement.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2621-08
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2017
    detail.hit.zdb_id: 2403378-9
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  • 6
    Online Resource
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    Mobile Cross-Slope Measurement Method Using Lidar Technology
    SAGE Publications ; 2013
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2367, No. 1 ( 2013-01), p. 53-59
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2367, No. 1 ( 2013-01), p. 53-59
    Abstract: An effective cross slope facilitates drainage on highways and prevents hydroplaning. There is a need for transportation agencies to identify and measure road sections that have noneffective cross slopes so that timely corrective maintenance can be performed. However, the traditional manual methods used by transportation agencies to measure cross slopes with a digital level are time-consuming and labor intensive; these methods are not feasible for conducting a network-level cross-slope measurement. A proposed mobile cross-slope measurement method uses emerging mobile lidar technology that can accurately and effectively conduct network-level cross-slope measurement at highway speeds. The proposed mobile cross-slope measurement method uses emerging lidar technology (lidar calibration, data acquisition, region of interest extraction, and cross-slope computation). A sensitivity study was conducted to determine the key parameter (i.e., the region of interest interval) for the proposed method. The accuracy and the repeatability of the proposed method were critically validated through testing in a controlled environment. A case study demonstrated the capability of the proposed method. The results from the controlled test show that the proposed method can achieve desirable accuracy with an average measurement difference of 0.088 from the digital-level measurements and a desirable level of repeatability with a standard deviation of less than 0.038 in three runs. The results of the case study show that the proposed method can be operated at highway speed and is promising for the assessment of network-level cross-slope adequacy.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2367-06
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2013
    detail.hit.zdb_id: 2403378-9
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  • 7
    Online Resource
    Online Resource
    Quantitative Performance Evaluation Algorithms for Pavement Distress Segmentation
    SAGE Publications ; 2010
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2153, No. 1 ( 2010-01), p. 106-113
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2153, No. 1 ( 2010-01), p. 106-113
    Abstract: Algorithms for pavement distress image segmentation are crucial to developing an automatic pavement distress detection and classification system. Many algorithms for pavement distress segmentation have been developed in the past decade; however, the lack of good methods to evaluate their performance quantitatively hinders the focused development of better segmentation algorithms. In this paper, a novel method is developed to quantitatively evaluate the performance of different pavement distress segmentation algorithms. This method uses the buffered Hausdorff distance to estimate the deviation of the cracks in the automatically segmented image from the ground truth cracks. The proposed method captures the local effectiveness of segmentation methods around the crack region without compromising its robustness to isolated pixel deviations caused by noise. Besides real pavement images, synthetic images simulating extreme pavement distress conditions are used to evaluate the capability of the proposed method and show its merits. The proposed method outperforms four other possible quantification methods and demonstrates its superior capability in providing a better score separation to distinguish the performance of different segmentation algorithms.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2153-12
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2010
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  • 8
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    Enhancing Decision-Making on Maintenance, Rehabilitation, and Reconstruction of Jointed Plain Concrete Pavements using Slab-Based Cracking Data and Life-Cycle Cost Analysis
    SAGE Publications ; 2020
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2674, No. 8 ( 2020-08), p. 511-522
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2674, No. 8 ( 2020-08), p. 511-522
    Abstract: Many jointed plain concrete pavements (JPCP) on critical roads in the United States are aged and have reached the end of their design lives. They thus require maintenance, rehabilitation, and reconstruction (MR & R) actions, which mainly involve slab replacement or lane reconstruction. Limited budgets challenge transportation agencies to determine the most cost-effective MR & R strategies, especially when life-cycle cost analysis (LCCA) is limited by the unreliable prediction of the pavement’s future needs. This paper proposes an enhanced LCCA-based methodology that utilizes slab-based cracking data collected using 3D laser technology, to select the best strategy for MR & R of JPCP by determining the timing and cost of slab replacement and lane reconstruction. By predicting pavement performance based on the current slab-based condition state using a Markov chain forecasting model, slab replacement projects are scheduled, and their feasibility is evaluated to determine the proper timing for lane reconstruction within the analysis period. LCCA is then conducted to select the alternative with the most cost-effective strategy for scheduling slab replacement and lane reconstruction projects. A case study is conducted on two 1-mi segments of I-16 in Georgia to validate the proposed methodology, followed by a sensitivity analysis to identify the input variables having a significant impact on the LCCA results. The developed framework proved its strength in determining the best MR & R strategy based on segment-level need assessment, which is utilized to perform “what if” analyses that evaluate different scenarios of project scheduling and accommodate the requirements and limitations defined by transportation agencies.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/0361198120925068
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
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  • 9
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    Quantifying Raveling Using 3D Technology with Loss of Aggregates as a New Performance Indicator
    MDPI AG ; 2022
    In:  Sustainability Vol. 14, No. 12 ( 2022-06-19), p. 7471-
    Details
    In: Sustainability, MDPI AG, Vol. 14, No. 12 ( 2022-06-19), p. 7471-
    Abstract: Pavement raveling is one of the predominant distresses in the United States that impacts roadway safety and driver comfort on open-graded friction course (OGFC) pavements. Raveling specific treatments, such as fog seal and micro-milling the OGFC layer, can prolong pavement life and reduce resurfacing costs and environmental impact. However, with the current qualitative condition assessment methods (which rate pavements at Severity Levels 1–3 or as light, moderate, or severe), it is difficult to determine the optimal timing for these raveling treatments to be most effective. Therefore, there is an urgent need to develop a method to quantitatively evaluate the raveling condition. While 3D pavement technology provides opportunities for quantifying pavement raveling conditions using 3D pavement surface data, there are two main challenges for quantifying pavement raveling: (1) estimating a reference surface that represents the pavement without any raveling so that the actual pavement can be compared to the reference surface to quantify the raveling, and (2) obtaining pavement images with quantified raveling conditions (aggregate loss volume) for validation. This paper proposes a method with the loss of aggregate as a new performance indicator to automatically quantify raveling using 3D pavement surface data already collected by transportation agencies for pavement evaluation. The proposed method is validated using pavement images (with known aggregate loss) from simulated pavement mats fabricated in the lab and synthetic pavement images obtained by procedural generation. The proposed method consists of (1) 3D data acquisition; (2) pre-processing with (a) outlier removal and image smoothing, (b) two-sensor image stitching, and (c) range image rectification; (3) raveling detection using (a) region of interest selection, (b) reference surface estimation, (c) potential aggregate loss identification, and (d) noise removal; and (4) aggregate loss quantification. The validation results show a strong correlation (R = 0.99) between the computed aggregate loss and the expected aggregate loss. Better performance was observed with the proposed method than with other methods (such as the watershed method and the model fitting method). The proposed method provides a cost-effective means to quantify the loss of aggregates in support of quantitative raveling condition forecasting by leveraging 3D pavement data already collected by transportation agencies.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su14127471
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518383-7
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  • 10
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    Enhanced Roadway Inventory Using a 2-D Sign Video Image Recognition Algorithm
    Wiley ; 2006
    In:  Computer-Aided Civil and Infrastructure Engineering Vol. 21, No. 5 ( 2006-07), p. 369-382
    Details
    In: Computer-Aided Civil and Infrastructure Engineering, Wiley, Vol. 21, No. 5 ( 2006-07), p. 369-382
    Type of Medium: Online Resource
    ISSN: 1093-9687 , 1467-8667
    URL: Issue
    URL: Article
    DOI: 10.1111/mice.2006.21.issue-5
    DOI: 10.1111/j.1467-8667.2006.00443.x
    Language: English
    Publisher: Wiley
    Publication Date: 2006
    detail.hit.zdb_id: 2016953-X
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