• International Journal of Highway Engineering
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• v.14 no.1
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• pp.85-94
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• 2012

The term "incident duration time" is defined as the time from the occurrence of incident to the completion of the handling process. Reductions in incident durations minimize damages by traffic accidents. This study aims to develop models to identify factors that influence incident duration by investigating traffic accidents on highways. For this purpose, four models were established including an integrated model (Model 1) incorporating all accident data and detailed models (Model 2, 3 and 4) analyzing accidents by location such as basic section, bridges and tunnels. The result suggested that the location of incident influences incident duration and the time of arrival of accident treatment vehicles is the most sensitive factor. Also, significant implications were identified with regard to vehicle to vehicle accidents and accidents by trucks, in night or in weekends. It is expected that the result of this study can be used as important information to develop future policies to manage traffic accidents.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.163-171
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• 2012

High resolution satellite images have been used for building and road system analysis, landscape analysis, and ecological assessment for several years. However, in high resolution satellite images, shadows are necessarily cast by manmade objects such as buildings and over-pass bridges. This paper develops the shadow extraction procedures in urban area including various land-use classes, and the extracted shadow areas are evaluated by a manually digitized shadow map. For the shadow extraction, the Canny edge operator and the dilation filter are applied to make building edge buffer area. Also, the object-based segmentation was performed using Gram-Schmitt fusion image, and spectral and spatial parameters are calculated from the segmentation results. Finally, we proposed appropriate parameters and extraction rules for the shadow extraction. The accuracy of the shadow extraction results from the various assessment indices is 80% to 90%.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.6
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• pp.51-63
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• 1996

This study is about the problems found in the process of the current governments planning rural settlement area development. As a measure to solve them, It proposed the analysis method of village characteristic in terms of standard score and tried to use this method as a basic material in planning more effective rural settlement area development. On the basis of the above analysis, which is an objective basic material to solve the problems revealed in the process of the bottom-up development planning by the residents' demands, It shows the following conclusion about what method should be applied to each part according to a village's characteristics and its development level. 1. Accessibility can be a basic material for setting the local area, analyzing its settlement system, and them such development facilities as village-linking roads, rural road, or various kinds of bridges and determining the investment priority. 2. With the index of the industrial basis, we can see what village has plenty of social, economical resources including advanced industrial facilities and looking into the advance level of the industrial basis, we can get some information about determining the local area development direction such as estashing the plan to build a farm product gathering center, a collective work place, storage facilities, and special housing development. 3. Since the issue about living environment is raising it's head, compared to weakened agricultural competitive power, with the analysis of this living environment, we can get an objective basic material for solving problems caused by the local egoism and the effective investment strategy of the limited resources. Therefore, It is necessary that we should abstain from expert-centered planning and formal public opinion-collecting and on the basis of this analytic result, we should plan development. We need to continue our research about index selecting and differentiation, weight etc. and using these analysis methods, we should make up a systematic development plan by analyzing village characteristics and setting the development direction.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.1-11
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• 2016

PURPOSES : This study estimated the load effect of a single heavy truck to develop a live load model for the design and assessment of bridges located on an expressway with a limited truck entry weight. METHODS : The statistical estimation methods for the live load effect acting on a bridge by a heavy vehicle are reviewed, and applications using the actual measurement data for trucks traveling on an expressway are presented. The weight estimation of a single vehicle and its effect on a bridge are fundamental elements in the construction of a live load model. Two statistical estimation methods for the application of extrapolation in a probabilistic study and an additional estimation method that adopts the extreme value theory are reviewed. RESULTS : The proposed methods are applied to the traffic data measured on an expressway. All of the estimation methods yield similar results using the data measured when the weight limit has been relatively well observed because of the rigid enforcement of the weight regulation. On the other hand, when the estimations are made using overweight traffic data, the resulting values differ with the estimation method. CONCLUSIONS : The estimation methods based on the extreme distribution theory and the modified procedure presented in this paper can yield reasonable values for the maximum weight of a single truck, which can be applied in both the design and evaluation of a bridge on an expressway.

• Smart Structures and Systems
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• v.24 no.6
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• pp.723-732
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• 2019

Globally road transport networks are subjected to continuous levels of stress from increasing loading and environmental effects. As the most popular mean of transport in the UK the condition of this civil infrastructure is a key indicator of economic growth and productivity. Structural Health Monitoring (SHM) systems can provide a valuable insight to the true condition of our aging infrastructure. In particular, monitoring of the displacement of a bridge structure under live loading can provide an accurate descriptor of bridge condition. In the past B-WIM systems have been used to collect traffic data and hence provide an indicator of bridge condition, however the use of such systems can be restricted by bridge type, assess issues and cost limitations. This research provides a non-contact low cost AI based solution for vehicle classification and associated bridge displacement using computer vision methods. Convolutional neural networks (CNNs) have been adapted to develop the QUBYOLO vehicle classification method from recorded traffic images. This vehicle classification was then accurately related to the corresponding bridge response obtained under live loading using non-contact methods. The successful identification of multiple vehicle types during field testing has shown that QUBYOLO is suitable for the fine-grained vehicle classification required to identify applied load to a bridge structure. The process of displacement analysis and vehicle classification for the purposes of load identification which was used in this research adds to the body of knowledge on the monitoring of existing bridge structures, particularly long span bridges, and establishes the significant potential of computer vision and Deep Learning to provide dependable results on the real response of our infrastructure to existing and potential increased loading.

• International journal of steel structures
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• v.18 no.5
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• pp.1617-1630
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• 2018

The crucial differences between conventional rail with split-type connectors and continuous welded rails are axial stress in the longitudinal direction and stability, as well as other issues generated under the influence of loading effects. Longitudinal stresses generated in continuously welded rails on railway bridges are strongly influenced by the nonlinear behavior of the supporting system comprising sleepers and ballasts. Thus, the track structure interaction cannot be neglected. The rail-support system mentioned above has properties of non-uniform material distribution and uncertainty of construction quality. The linear elastic hypothesis therefore cannot correctly evaluate the stress distribution within the rails. The aim of this study is to apply the nonlinear finite element method using the nonlinear coupling interface between the track and structural model and to illustrate the welded rail behavior under the loading effect and uncertain factors of the ballast. Numerical results of nonlinear finite analysis with a three-dimensional solid and frame element model are presented for a typical track-bridge system. A composite plate girder, modeled by solid and shell elements, is also analyzed to consider the behavior of the welded rail. The analysis result showed buckling under the independent calculations of load cases, including 'temperature change', 'bending of the supporting structure', and 'braking' of the railway vehicle. A parametric study of the load combination method and the loading sequence is also included in this analysis.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.205-222
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• 2022

This study aims to improve the information service so that construction engineers and construction project participants without specialized knowledge can easily understand the important words and the interrelationships between them in construction practice. To this end, using text mining and network centrality, the frequency of occurrence of words, topic modeling, and network centrality in construction practice information such as technical information, case information, and cost reduction, which are most used in the Construction Technology Digital Library, were analyzed. Through this analysis, design, construction, project management, specifications, standards, and maintenance related to road construction such as roads, pavements, bridges, and tunnels were identified as important in construction practice. In addition, correlations were analyzed for words with high importance by measuring Degree Centrality and Eigenvector Centrality. The result was that more useful information could be provided if the technical information was expanded. Finally, we presented the limitations of the study results and additional studies according to the limitations.

• Structural Monitoring and Maintenance
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• v.9 no.1
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• pp.43-57
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• 2022

One of the instances which demand structural engineer's greatest attention and upgradation is the changing live load requirement in bridge design code. The challenge increases in developing countries as the pace of infrastructural growth is being catered by the respective country codes with bigger and heavier vehicles to be considered in the design. This paper presents the case study of India where Indian Roads Congress (IRC) codes in its revised version from 2014 to 2017 introduced massive Special vehicle (SV) around 40 m long and weighing 3850 kN to be considered in the design of road bridges. The code does not specify the minimum distance between successive special vehicles unlike other loading classes and hence the consequences of it form the motivation for this study. The effect of SV in comparison with Class 70R, Class AA, Class A, and Class B loading is studied based on the maximum bending moment with moving load applied in Autodesk Robot Structural Analysis. The spans considered in the analysis varied from 10 m to 1991 m corresponding to the span of Akashi Kaikyo Bridge (longest bridge span in the world). A total of 182 analyses for 7 types of vehicles (class B, class A, class 70R tracked, class 70R wheeled, class AA tracked, AA wheeled, and Special vehicle) on 26 different span lengths is carried out. The span corresponding to other vehicles which would equal the bending moment of a single SV is presented along with a comparison relative to Standard Uniformly Distributed Load. Further, the results are presented by introducing a new parameter named Intensity Factor which is proven to relate the effect of axle spacing of vehicle on the normalized bending moment developed.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.50-57
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• 2023

Autonomous driving technologies have been gradually improved for road traffic owing to the development of artificial intelligence. Since the truck platooning is beneficial in terms of the associated transporting expenses, the Connected-Automated Vehicle technology is rapidly evolving. The structural performance is, however, rarely investigated to capture the effect of truck platooning on civil infrastructures.In this study, the dynamic behavior of bridges under truck platooning was investigated, and the amplification factor of responses was estimated considering several parameters associated with the driving conditions. Artificial intelligence techniques were used to estimate the maximum response of the mid span of a bridge as the platooning vehicles passing, and the importance of the parameters was evaluated. The most suitable algorithm was selected by evaluating the consistency of the estimated displacement.