• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.155-166
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• 2002

Since 1990s. there has been an increasing number of traffic accidents at intersection. which requires more urgent measures to insure safety on intersection. This study set out to analyze the road conditions, traffic conditions and traffic operation conditions on signalized intersection. to identify the elements that would impose obstructions in safety, and to develop a traffic accident prediction model to evaluate the safety of an intersection using the cop relation between the elements and an accident. In addition, the focus was made on suggesting appropriate traffic safety policies by dealing with the danger elements in advance and on enhancing the safety on the intersection in developing a traffic accident prediction model fir a signalized intersection. The data for the study was collected at an intersection located in Wonju city from January to December 2001. It consisted of the number of accidents, the road conditions, the traffic conditions, and the traffic operation conditions at the intersection. The collected data was first statistically analyzed and then the results identified the elements that had close correlations with accidents. They included the area pattern, the use of land, the bus stopping activities, the parking and stopping activities on the road, the total volume, the turning volume, the number of lanes, the width of the road, the intersection area, the cycle, the sight distance, and the turning radius. These elements were used in the second correlation analysis. The significant level was 95% or higher in all of them. There were few correlations between independent variables. The variables that affected the accident rate were the number of lanes, the turning radius, the sight distance and the cycle, which were used to develop a traffic accident prediction model formula considering their distribution. The model formula was compared with a general linear regression model in accuracy. In addition, the statistics of domestic accidents were investigated to analyze the distribution of the accidents and to classify intersections according to the risk level. Finally, the results were applied to the Spearman-rank correlation coefficient to see if the model was appropriate. As a result, the coefficient of determination was highly significant with the value of 0.985 and the ranks among the intersections according to the risk level were appropriate too. The actual number of accidents and the predicted ones were compared in terms of the risk level and they were about the same in the risk level for 80% of the intersections.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.200-215
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• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

• 전자공학회논문지 IE
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• v.43 no.1
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• pp.32-38
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• 2006

When induction motor moves, power quality decline of line is risen seriously because provoking voltage drop the moment to system power supply by excessive moving current as well as power-factor drop in case drive by light-load because current reaches in 6 times $\sim$ 8 times of rated current. In this paper, a modeling did an distribution system 13 bus type model and induction machine load presents in IEEE using a PSCAD/EMTDE package, and it displayed an accident conspiracy and a compensating factor of DSTATCOM through simulation show.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.1-11
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• 2016

The purpose of this study is to contribute the use of special taxi for the transportation vulnerable such as elderly and pregnant woman in terms of improving transportation mobility and extending social participation. We analyzed the DB users of STS system operating in Suwon, and surveyed the preference statement. Specifically, we have built transportation mode choice models for the elderly and pregnant woman, and then we drew the activating STS plan by comparing influence factors for each model. Based on the results of the study, 23% of STS user was the elderly people and pregnant women, 31% of user was for hospital passage purpose, and short-haul passage within 2 ~ 5km was 70% level of the passage. According to preference survey results between STS and Bus, fare was the highest impact factor in the mode choices for the elderly, and the participants who are older and car owners have been found to prefer the special taxi. For the pregnant woman, travel time and fare were the main influence factors of choices, and it was discovered that they preferred the special taxi when they are car owners and trips was frequented. Also, if the fare of special taxi is about 70% of the regular taxi fare, The share rates of Special Taxi comparing to bus for the elderly and pregnant woman are analyzed to be 51.1% and 63.6% each. Therefore, the adjustment of the fare would be effective to encourage the use of the special taxi. The results of this study can be used as a basis for establishing the rational fare structure of the special taxi.

• Spatial Information Research
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• v.19 no.4
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• pp.11-20
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• 2011

In accordance with low carbon and green growth paradigm, a subway is one of major public transit systems for resolving traffic congestion and decreasing traffic accidents. In addition, as subway networks expand, passengers' travel pattern in the subway network change and consequently affect the urban structure. Generally, new subway route has been planned and developed, mainly considering a travel demand forecast. However, it is desired to conduct an empirical analysis on the forecast model regarding change of travel accessibility and passenger demand pattern according to new subway line. Therefore, in this paper, an alternative method, developed based upon a spatial syntax model, is proposed for evaluating new subway route in terms of passenger's mobility and network accessibility. In a case study, we constructed subway network data, mainly targeting the no 9 subway line opened in 2009. With an axial-map analysis, we calculated spatial characteristics to describe topological movement interface. We then analyzed actual modal shift and change on demand of passengers through the number of subway passenger between subway stations and the number of passenger according to comparative bus line from Smart Card to validate suggested methods. Results show that the proposed method provides quantitative means of visualizing passenger flow in subway route planning and of analyzing the time-space characteristics of network. Also, it is expected that the proposed method can be utilized for predicting a passengers' pattern and its impact on public transportation.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.13-25
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• 2016

High-speed railway (Korea Train Express) has had a deep impact on the regional economy of Korea. Current high-speed rail research is mostly theoretical, there is a lack of quantitative research using a precise algorithm to study the effect of high-speed railway on the regional economy. This paper analyses the influence of high-speed rail on the regional economy, with a focus on the Daegu area. Quantitative analysis using department store indexes and regional medical records is performed to calculate the economic influence of high-speed rail. The result shows that high-speed railway effects the regional economy though regional consumption growth and medical care trends.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.41-48
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• 2004

We may consider the inducement of demand to public transportation as a solution to relieve traffic congestion and pollution. Subway has merits as moving on schedule, transporting more people than bus. But subway is required a vast investment in the early stage of construction has a huge debt. So it runs into red figures, and on this account, services of subway are falling more and more. Development of subway's operation cost function is useful to understand structure of subway's operation and catch the relations of operation cost and actual results. In addition, we can present the policy that is a helpful to the operation as development of operation cost function. But there are short of studies about operation cost deal with a subway comparison with local train. Because local train has many lines and data, on the other hand, subway has one to four lines and less data. Most of previous studies sought the operation cost function of Seoul. So this study aimed to develop and apply the operation cost function of Seoul, Incheon, Busan and Daegu area using full allocation method. In this study, we considered the number of passengers, track-km, train-km, revenue as actual results. By appling the operation cost function, we compared the average cost of each city and confirmed the existence of economies of scale about the number of passengers, train-km.