• Journal of Korean Society of Transportation
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• v.31 no.6
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• pp.3-11
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• 2013

Under the consumption of bad weather situation affects traffic flows, the study scope is focused on highway capacity and speed variations among other highway traffic flow characteristic changes according to snowfall density. Thus, this study carried out through the data collection and statistical analysis by focusing on capacity and speed changes. Traffic volume, speed and density were selected as factors to explain the property change of a traffic flow for analysis, and 7 basic sections such as 3 highways in Gyeonggi-do and 4 highways near the meteorological observatory were selected as survey points for data collection. Snowfall levels were classified into 3 steps(Light, Medium, Heavy Snow) to analyze the capacity change by snowfall levels. As a result of analysis, the change of capacity depending on snowfall levels decreased 13.2% in case of light snow compared to a good weather, 18.6% in case of medium snow and 32.0% in case of heavy snow, so the capacity reduction rate increased as the snowfall level increased. The worsening weather appeared to have a very big possibility to act as a factor to reduce the operational efficiency of a road, so a road design and operation method considering this should be presented in the future.

• Journal of the Korean Geotechnical Society
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• v.35 no.12
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• pp.69-89
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• 2019

Design chart solution and table solution were proposed by Choi et al. (2019a), which conducted a parametric numerical study for the bored PHC piles socketed into weathered rocks through sandy soil layers. Based on the Choi et al. (2019a), the new prediction formulae for mobilized capacity components such as total capacity, total skin friction and skin friction of sand at the settlement of 5% pile diameter were proposed in this study. The proposed prediction formulae (EQ-G1) considers pile diameter, relative embedment length and ${\bar{N}}$ (i.e, corrected N) value and their verification results are as follows. The SRF calculated from the new proposed design method was 71~94%, which are greatly improved compared with results by the existing design method. The design efficiency of bearing capacity was in the range of reasonable design except 4 cases, and the design efficiency of the PHC pile was evaluated as 85%. Therefore, it is possible that allowable compressive load (P_all) of PHC pile can be utilized in the resonable design by means of the new proposed method using EQ-G1 equations. And the other new proposed equations of EQ-G2-3 can be utilized approximately in calculation of axial compressive bearing capacity components for prebored PHC pile.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1287-1295
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• 2015

This research is the study on the comparative evaluation of SPC (Staggered Pedestrian Crossings) vs PC (Pedestrian Crossings) using risk analysis. Accident factor was elicited by survey of driver's and pedestrian's at SPC & PC. I estimated the weight of a risk of violation and a mental burden by AHP (Analytic Hierarchy Process) and compared degree of risk at SPC AND PC. In conclusion, a new alternative plan of a pedestrian crossing system, staggered pedestrian crossing which plays an important role in traffic flow, pedestrian's crossings which plats an important role in traffic flow, pedestrian's convenience and traffic safer is sager than pedestrian crossings the degree of risk used this study doesn't imply an measure of the number of accident and the rate of accident, in estimating the degree of risk of pedestrian crossings, we should analyze more data of accident, behaviors, and road circumstance to include driver's and pedestrian's violation behavior in an estimate index.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1329-1338
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• 2015

This article aims to develop model for the right policy Tools available from the cause analysis regarding the regional differences of subway modal split in Seoul metropolitan area. This allows two major factors of the most influential subway modal split to be proved and Portfolio Analysis is conducted. The results are as follows. Firstly, the two primary factors affecting subway modal split were shown as subway adjacent area and local line bus. It signifies that expansion of subway adjacent area, establishing the number of the subway stations and increase of local line bus are required in order to improve a diminishing subway modal split. Following that, pattern of the improvement to strengthen better subway connections are classified according to the two areas which are Concentration Area of Improvement in Subway Station Area (CAISSA) and Concentration Area of Improvement in Local Bus (CAILB). Our study revealed that Ganbukgu, Seodaemungu, Geumcheongu, and Gwanakgu were selected as the area of CAILB and Songpagu, and Junggu were selected as the area of CAISSA. As all things are considered, transportation policy makers should be taken into account in the two main factors driven by our study according to types in order to enhance the future subway share proportion.

• Journal of the Korean Geotechnical Society
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• v.35 no.11
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• pp.75-95
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• 2019

The numerical analysis on PHC piles socketed into weathered rocks through sandy soil layers was conducted to propose the table solution or the chart solution to obtain the mobilization capacity. The mobilization capacity was determined at the settlement of 5% pile diameter and applied a safety factor of 3.0. In order to utilize the excellent compressive strength of the PHC pile effectively, it is recommended that the allowable bearing capacity of ground would be designed to be more than the long-term allowable compressive pile load. A procedure for determining an allowable pile capacity for PHC piles socketed into weathered rocks through sandy soil layers is given by the sum of the allowable skin friction of the sandy soil layer and the weathered rock layer and the allowable end bearing capacity of the weathered rock layer. The design efficiency of the PHC pile is about 85% at the reasonable design stage in the verification of the newly proposed method. Thus, long-term allowable compressive load (P_all) level of PHC piles can be utilized in the optimal design stage.

• Journal of Korean Society of Transportation
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• v.34 no.3
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• pp.278-290
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• 2016

Maximum traffic flow rate is an important performance measure of operational status in transport networks, and has been considered as a key parameter for transportation operation since a bottleneck in congestion decreases maximum traffic flow rate. Although previous studies for traffic flow analysis have been widely conducted, a detection method for changes in dynamic traffic flow has been still veiled. This paper explores the dynamic traffic flow detection that can be utilized for various traffic operational strategies. Turning point analysis (TPA), as a statistical method, is applied to detect the changes in traffic flow rate. In TPA, Bayesian approach is employed and vehicle arrival is assumed to follow Poisson distribution. To examine the performance of the TPA method, traffic flow data from Jayuro urban expressway were obtained and applied. We propose a novel methodology to detect turning points of dynamic traffic flow in real time using TPA. The results showed that the turning points identified in real-time detected the changes in traffic flow rate. We expect that the proposed methodology has wide application in traffic operation systems such as ramp-metering and variable lane control.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.377-393
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• 2016

Vehicle emissions have been known as a critical factor to give a negative impact on the public health. In particular, particulate matters(PM) and NOx are highly related with respiratory diseases such as asthma. This study aimed at analyzing spatio-temporal patterns of PM and NOx generated from urban freeway traffic. MOVES, which is a well-known emission analysis tool presented by US Environmental Protection Agency(EPA), was applied to estimate PM and NOx based on traffic volume and speed data obtained from Seoul Outer Ring Expressway during January~June, 2012. K-means clustering analysis was used for categorizing the Level of Vehicle Emissions(LOVE) to support more systematical identification of the significance of emissions. Then, spatio-temporal analyses of estimated emissions were conducted by LOVE. Finally, this study proposed a set of strategies to reduce both PM and NOx to enhance public health based on analysis results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.39-57
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• 2018

The purpose of this study was to construct an artificial intelligence model that learns and estimates the relationship between vehicle queue length and link travel time in urban areas. The vehicle queue length estimation model is modeled by three models. First of all, classify whether vehicle queue is a link overflow and estimate the vehicle queue length in the link overflow and non-overflow situations. Deep learning model is implemented as Tensorflow. All models are based DNN structure, and network structure which shows minimum error after learning and testing is selected by diversifying hidden layer and node number. The accuracy of the vehicle queue link overflow classification model was 98%, and the error of the vehicle queue estimation model in case of non-overflow and overflow situation was less than 15% and less than 5%, respectively. The average error per link was about 12%. Compared with the detecting data-based method, the error was reduced by about 39%.

• Journal of Environmental Impact Assessment
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• v.19 no.5
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• pp.475-481
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• 2010

Lots of pollutants typically originating from urban transportation are accumulating on the paved surfaces during dry periods and are washed-off directly to the river during a storm. Also, paved surfaces are contributing to increase in peak flows and volume of stormwater flows. These are the main reasons why the water quality of rivers and lakes remain polluted and still below standards. Currently, several management practices are being applied in developed countries but the design standards are still lacking. This research was conducted to develop a treatment technology that can be useful to address the problems concerning runoff quality and quantity. A lab scale infiltration device consisting of a pretreatment tank and media zone was designed and tested for various flow regimes characterizing the low, average and high intensity rainfall. Based on the experiments, the high intensity flow resulted to increase in outflow event mean concentration (EMC) of pollutants, about twice as much as the average outflow EMC. However, 78 to 88% of the total suspended solids were captured and retained in the pretreatment tank because of sedimentation. The removal of heavy metals such as zinc and lead was greatly affected by the vertical placement of woodchip layer prior to the media zone. It was observed that the high carbon content (almost 50%) in the woodchip provided opportunity for enhancing its uptake of metal by adsorption. The findings implied that the reduction of pollutants can be greatly achieved by means of proper pretreatment to allow for settling of particles with a combination of using high carbon source media like woodchip and a geotextile mat to reduce the flow before filtering into the media zone and finally discharging to the drainage system.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.158-167
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• 2016

This study evaluates potential sources of errors in k-NN(k-nearest neighbor) algorithm such as procedures, variables, and input data. Previous research has been thoroughly reviewed for understanding fundamentals of k-NN algorithm that has been widely used for short-term traffic states prediction. The framework of this algorithm commonly includes historical data smoothing, pattern database, similarity measure, k-value, and prediction horizon. The outcomes of this study suggests that: i) historical data smoothing is recommended to reduce random noise of measured traffic data; ii) the historical database should contain traffic state information on both normal and event conditions; and iii) trial and error method can improve the prediction accuracy by better searching for the optimum input time series and k-value. The study results also demonstrates that predicted error increases with the duration of prediction horizon and rapidly changing traffic states.