• Journal of Climate Change Research
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• v.7 no.2
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• pp.177-184
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• 2016

Recently, the need for technology development of commercial vehicle fuel consumption has emerged. Fuel economy improvement of transport equipment and transportation efficiency, and increasing attention to the logistics cost reduction measures. Increasing attention to the logistics cost reduction measures by fuel economy improvement of transport equipment and transportation efficiency. In this study, we have installed aerodynamic reduction device (side skirt, boat tail) to 14.5 ton cargo trucks and 45 ft tractor-trailers. And the fuel consumption was compared installed before and after. Fuel economy assessment for the aerodynamic reduction value device was tested by modifying the SAE J1321 Joint TMC/SAE Fuel Consumption Test Procedure - Type II test in according domestic situation. Greenhouse gas reductions were calculated in accordance with the scenario, including fuel consumption test results. When the 14.5 ton cargo trucks has been equipped with side skirts and boat tail, it confirmed the improvement in fuel efficiency of 4.72%. One Heavy-duty truck's the annual greenhouse gas reductions value are $6.86ton\;CO_2\;eq$. And if applying the technology to more than 50% of registered 15 ton trucks, greenhouse gas reductions are calculated as $686,826ton\;CO_2\;eq./yr$.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.645-657
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• 2021

Along with the rapid development of the economy, the urban scale has extended rapidly, leading to the formation of different types of urban function districts (UFDs), such as central business, residential and industrial districts. Recognizing the spatial distributions of these districts is of great significance to manage the evolving role of urban planning and further help in developing reliable urban planning programs. In this paper, we propose an automatic UFD division method based on big data analysis of point of interest (POI) data. Considering that the distribution of POI data is unbalanced in a geographic space, a dichotomy-based data retrieval method was used to improve the efficiency of the data crawling process. Further, a POI spatial feature analysis method based on the mean shift algorithm is proposed, where data points with similar attributive characteristics are clustered to form the function districts. The proposed method was thoroughly tested in an actual urban case scenario and the results show its superior performance. Further, the suitability of fit to practical situations reaches 88.4%, demonstrating a reasonable UFD division result.

• Structural Engineering and Mechanics
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• v.88 no.4
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• pp.323-334
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• 2023

The submerged floating tunnel (SFT) infrastructure has been regarded as an emerging technology that efficiently and safely connects land and islands. The SFT route problem is an essential part of the SFT planning and design phase, with significant impacts on the surrounding environment. This study aims to develop an optimization model considering transportation and structure factors. The SFT routing problem was optimized based on two objective functions, i.e., minimizing total travel time and cumulative strains, using NSGA-II. The proposed model was applied to the section from Mokpo to Jeju Island using road network and wave observation data. As a result of the proposed model, a Pareto optimum curve was obtained, showing a negative correlation between the total travel time and cumulative strain. Based on the inflection points on the Pareto optimum curve, four optimal SFT routes were selected and compared to identify the pros and cons. The travel time savings of the four selected alternatives were estimated to range from 9.9% to 10.5% compared to the non-implemented scenario. In terms of demand, there was a substantial shift in the number of travel and freight trips from airways to railways and roadways. Cumulative strain, calculated based on SFT distance, support structure, and wave energy, was found to be low when the route passed through small islands. The proposed model helps decision-making in the planning and design phases of SFT projects, ultimately contributing to the progress of a safe, efficient, and sustainable SFT infrastructure.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.545-556
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• 2017

Various assessment indexes have been developed and utilized to evaluate the driver workload. However, existing workload assessment indexes do not fully reflect driving habits and driving patterns of individual drivers. In addition, there exists significant differences in the amount of workload experienced by a driver and the ability to overcome the driver's workload. To overcome these limitations associated with existing indexes, this study has developed a novel workload assessment index to reflect an individual driver's driving pattern. An average of the absolute values of the steering velocity for each driver are set as a threshold value in order to reflect the driving patterns of individual drivers. Further, the sum of the areas of the steering velocities exceeding the threshold value, which is defined as erratic steering area (ESA) in this study, was quantified. The developed ESA index is applied in evaluating the driver workload of manually driven vehicles in automated vehicle platooning environments. Driving simulation experiments are conducted to collect drivers' responsive behavior data which are used for exploring the relationship between the NASA-TLX score and the ESA by the correlation analysis. As a result, ESA is found to have the greatest correlation with the NASA-TLX score among the various driver workload evaluation indexes in the lane change scenario, confirming the usefulness of ESA.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.71-80
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• 2012

This research suggested a real-time traffic signal control algorithm using individual vehicle travel times on an isolated signal intersection. To collect IDs and passing times from individual vehicles, space-based surveillance systems such as DSRC were adopted. This research developed models to estimate arrival flow rates, delays, and the change rate in delay, by using individual vehicle's travel time data. This real-time signal control algorithm could determine optimal traffic signal timings that minimize intersection delay, based on a linear programming. A micro simulation analysis using CORSIM and RUN TIME EXTENSION verified saturated intersection conditions, and determined the optimal traffic signal timings that minimize intersection delay. In addition, the performance of algorithm varying according to market penetration was examined. In spite of limited results from a specific scenario, this algorithm turned out to be effective as long as the probe rate exceeds 40 percent. Recently, space-based traffic surveillance systems are being installed by various projects, such as Hi-pass, Advanced Transportation Management System (ATMS) and Urban Transportation Information System (UTIS) in Korea. This research has an important significance in that the propose algorithm is a new methodology that accepts the space-based traffic surveillance system in real-time signal operations.

• Journal of Korean Society of Transportation
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• v.34 no.4
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• pp.318-329
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• 2016

There has been a growing interest on the effect of volcanic eruption on the aviation safety, air travel and economy especially after the eruption of Eyjafjallajokull in Iceland. Since volcanic eruption is influential on a large geographic region, the effect usually extends to other neighboring countries. Korea also has an active volcano named Mountain Baekdu. Hence, the need to estimate in advance the quantitative impact of the potential eruption of Mt. Baekdu on South Korean air transportation system. However, previous studies with quantitative estimation were confined to the calculation of the direct economic loss from shut down of the airports, grounding of airlines, and trade deficits caused by the eruption. Therefore, this paper introduces a new approach to assess more accurate impact simultaneously considering volcanic ash dispersal and aviation routes. This approach is then applied to a virtual scenario to predict the damage to air traffic. With further development, this method can help estimate the damage in the air transportation industry in more accurate and faster ways. Prediction outcomes can also be utilized in setting up the emergency response plan for the air transportation industry and contribute to the creation of more proactive and predictive measures in the future.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.53-66
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• 2008

This research is to the establishment of a conceptual framework that supports road characteristic classification from a new point of view in order to complement of the existing road functional classification and examine of traffic pattern. The road characteristic classification(RCC) is expected to use important performance criteria that produced a policy guidelines for transportation planning and operational management. For this study, the traffic data used the permanent traffic counters(PTCs) located within the national highway between 2002 and 2006. The research has described for a systematic review and assessment of how exploratory factor analysis should be applied from 12 explanatory variables. The optimal number of components and clusters are determined by interpretation of the factor analysis results. As a result, the scenario including all 12 explanatory variables is better than other scenarios. The four components is produced the optimal number of factors. This research made contributions to the understanding of the exploratory factor analysis for the road characteristic classification, further applying the objective input data for various analysis method, such as cluster analysis, regression analysis and discriminant analysis.

• Journal of Navigation and Port Research
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• v.44 no.5
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• pp.382-391
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• 2020

In line with the trend of global transport volume which has increased rapidly over the years, internal transportation in seaports is always conducted with high frequency. Thus, there is always much potential for traffic jams as well as high transportation costs and emissions. Many efforts have been initiated to streamline the inter-terminal container transport (ITT) through the development of automated vehicles and equipment as well as using private transport facilities to overcome these limitations. The purpose of this paper to develop a framework to design, analyze, and validate the efficiency of a new ITT system in a port area based on the monorail network and automatic vehicles. First, the number of shuttles and loaders was determined depending on the transport demand scenario. Next, a simulation model was applied to evaluate the system performance as well as gain more insight into the working process of the ITT system. Finally, by setting goals for the performance indicators, the results showed that the system was highly efficient with 100% of the containers delivered to their destination on time. Besides, a series of other performance tracking was provided to provide insight into the system's capabilities.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.91-100
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• 2006

Travel Demand Forecasting (TDF) is an essential and critical process in the evaluation of the highway improvement Project. The four-step TDF Process has generally been used to forecast travel demand and analyze the effects of diverted travel demand based on the given Origin-Destination trips in the future. Transportation system improvements, however, generate more travel, Induced Travel Demand (ITD) or latent travel demand, which has not been considered in the project evaluation. The Purpose of this study Is to develop a model which can forecast the ITD applied theory of economics and the Program(I.D.A) which can be widely applied to project evaluation analysis. The Kang-Byun-Book-Ro expansion scenario is used to apply and analyze a real-world situation. The result highlights that as much as 15% of diverted travel demand is generated as ITD. The results of this study are expected to improve reliability of the project evaluation of the highway improvement Project.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.262-274
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• 2019

The purpose of this study is to estimate the minimum proportion of probe vehicles for obtaining expressway traffic information using VISSIM, a micro traffic simulation model, between Yongin IC and Yangji IC on Yeongdong Expressway. 7,200 scenarios were created for the experiment, and 40 scenarios were adopted using the Latin hypercube sampling method because it was difficult to perform all the scenarios through experiments. The reliability of the experiment was improved by adding a situation when the general situation and the accident situation exist. In the experiments, the average travel time of probe vehicles at different market penetration rates were compared with the average travel time of the entire vehicles. As a result, the minimum market penetration rate of probe vehicles for obtaining expressway traffic information was found to be 45%. In addition, it is estimated that 25% market penetration rate of probe vehicle can meet 70% of traffic situations in accident scenario.